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Susanna SPINSANTE

Pubblicazioni

Susanna SPINSANTE

 

243 pubblicazioni classificate nel seguente modo:

Nr. doc. Classificazioni
145 4 Contributo in Atti di Convegno (Proceeding)
67 1 Contributo su Rivista
26 2 Contributo in Volume
5 5 Altro
Anno Risorsa
Recognition of Activities of Daily Living Based on a Mobile Data Source Framework
Bio-inspired Neurocomputing. Studies in Computational Intelligence.
Autore/i: Pires, Ivan Miguel; Marques, Gonçalo; Garcia, Nuno M.; Flórez-Revuelta, Francisco; Teixeira, Maria Canavarro; Zdravevski, Eftim; Spinsante, Susanna
Editore: Springer
Luogo di pubblicazione: Singapore
Classificazione: 2 Contributo in Volume
Abstract: Most mobile devices include motion, magnetic, acoustic, and location sensors. These sensors can be used in the development of a framework for activities of daily living (ADL) and environment recognition. This framework is composed of the acquisition, processing, fusion, and data classification features. This study compares different implementations of artificial neural networks. The obtained results were 85.89% and 100% for the recognition of standard ADL and standing activities with Deep Neural Networks, respectively. Furthermore, the results present 86.50% for identification of the environments using Feedforward Neural Networks. Numerical results illustrate that the proposed framework can achieve robust performance from the incorporation of data fusion methods using mobile devices.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/283464 Collegamento a IRIS

2021 Performance evaluation of vibrational measurements through mmwave automotive radars
REMOTE SENSING
Autore/i: Ciattaglia, G.; De Santis, A.; Disha, D.; Spinsante, S.; Castellini, P.; Gambi, E.
Classificazione: 1 Contributo su Rivista
Abstract: Thanks to the availability of a significant amount of inexpensive commercial Frequency Modulated Continuous Wave Radar sensors, designed primarily for the automotive domain, it is interesting to understand if they can be used in alternative applications. It is well known that with a radar system it is possible to identify the micro-Doppler feature of a target, to detect the nature of the target itself (what the target is) or how it is vibrating. In fact, thanks to their high transmission frequency, large bandwidth and very short chirp signals, radars designed for automotive applications are able to provide sub-millimeter resolution and a large detection bandwidth, to the point that it is here proposed to exploit them in the vibrational analysis of a target. The aim is to evaluate what information on the vibrations can be extracted, and what are the performance obtainable. In the present work, the use of a commercial Frequency Modulated Continuous Wave radar is described, and the performances achieved in terms of displacement and vibration frequency measurement of the target are compared with the measurement results obtained through a laser vibrometer, considered as the reference instrument. The attained experimental results show that the radar under test and the reference laser vibrometer achieve comparable outcomes, even in a cluttered scenario.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/287204 Collegamento a IRIS

2020 A Swept-Sine Pulse Compression Procedure for an Effective Measurement of Intermodulation Distortion
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Autore/i: Burrascano, Pietro; Laureti, Stefano; Ricci, Marco; TERENZI, Alessandro; CECCHI, Stefania; SPINSANTE, Susanna; PIAZZA, Francesco
Classificazione: 1 Contributo su Rivista
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265697 Collegamento a IRIS

2020 Upper and lower treeline biogeographic patterns in semi‐arid pinyon‐juniper woodlands
JOURNAL OF BIOGEOGRAPHY
Autore/i: Garbarino, Matteo; Malandra, Francesco; Dilts, Thomas; Flake, Sam; Montalto, Luigi; Spinsante, Susanna; Weisberg, Peter J.
Classificazione: 1 Contributo su Rivista
Abstract: Aim: Upper and lower treelines are particularly exposed to a changing climate. It has been hypothesized that upper treelines are constrained by growing season temperature, whereas lower tree lines are water limited. We expect different causal mechanisms of upper versus lower tree line formation to generate distinct patterns of spatial heterogeneity. Here, we compare dynamics, spatial patterns and shape complexity of upper and lower tree lines of semi‐arid pinyon‐juniper woodlands. Location: Toiyabe Range of the Nevada Great Basin (western US). Taxon: Pinus monophylla Torr. & Frém. and Juniperus osteosperma (Torr.). Methods: Within 20 sample plots (10 along the upper and 10 along the lower tree line), we mapped tree canopies through photointerpretation of high‐resolution imagery. We performed point pattern analyses to compare the spatial arrangement of trees and used LANDSAT 30‐year time series and NDVI to understand the vegetation dynamics of these ecotones. We adopted the surface roughness method to measure tree line shape complexity. Results: Lower tree lines were denser and showed a stronger trend of increasing NDVI change over the 1984–2015 period. Trees at the lower tree line were more strongly aggregated than at the upper tree line at spatial scales ranging from 15 to 65 meters. Shape complexity was higher at upper tree lines, expressed by a higher mean surface roughness; however, the spatial structures of upper and lower tree lines were similar. Main conclusions: Upper tree line expansion of pinyon‐juniper woodlands in the study area has been limited and highly variable, but lower tree line downslope expansion into adjacent shrub steppe vegetation was evident. The expected difference between energy‐ and water‐limited tree lines did not manifest in the observed spatial structures. Differences in tree line shape complexity were not significant, although lower tree lines exhibited less complex shapes, likely because they have been more strongly influenced by anthropogenic factors.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/284043 Collegamento a IRIS

2020 Performance Evaluation of Vibrational Measurements Through mmWave Radars
Proc. of 2020 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AEROSPACE
Autore/i: Ciattaglia, Gianluca; De Santis, Adelmo; Disha, Deivis; Spinsante, Susanna; Castellini, Paolo; Gambi, Ennio
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Thanks to the availability of a significant amount of inexpensive commercial Frequency Modulated Continuous Wave Radar sensors, designed primarily for the automotive domain, it is interesting to understand if they can be used in alternative applications. Radars designed for automotive applications, in fact, thanks to their high transmission frequency, large bandwidth and very short chirp signals, are able to provide sub-millimeter resolution and a large detection bandwidth, to the point that it is here proposed to implement a vibrational analysis of a target and evaluate what information on the vibrations can be extracted, and the performance obtainable. In the present work the use of a commercial Frequency Modulated Continuous Wave radar is described, and the performances achieved in terms of target's displacement and frequency measurement are compared with the measurement results obtained through a laser vibrometer, considered as the reference instrument.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/283501 Collegamento a IRIS

2020 Pattern recognition techniques for the identification of activities of daily living using a mobile device accelerometer
ELECTRONICS
Autore/i: Pires, I. M.; Marques, G.; Garcia, N. M.; Florez-Revuelta, F.; Teixeira, M. C.; Zdravevski, E.; Spinsante, S.; Coimbra, M.
Classificazione: 1 Contributo su Rivista
Abstract: The application of pattern recognition techniques to data collected from accelerometers available in off-the-shelf devices, such as smartphones, allows for the automatic recognition of activities of daily living (ADLs). This data can be used later to create systems that monitor the behaviors of their users. The main contribution of this paper is to use artificial neural networks (ANN) for the recognition of ADLs with the data acquired from the sensors available in mobile devices. Firstly, before ANN training, the mobile device is used for data collection. After training, mobile devices are used to apply an ANN previously trained for the ADLs’ identification on a less restrictive computational platform. The motivation is to verify whether the overfitting problem can be solved using only the accelerometer data, which also requires less computational resources and reduces the energy expenditure of the mobile device when compared with the use of multiple sensors. This paper presents a method based on ANN for the recognition of a defined set of ADLs. It provides a comparative study of different implementations of ANN to choose the most appropriate method for ADLs identification. The results show the accuracy of 85.89% using deep neural networks (DNN).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/281594 Collegamento a IRIS

2020 Impact of Wearable Measurement Properties and Data Quality on ADLs Classification Accuracy
IEEE SENSORS JOURNAL
Autore/i: Poli, A.; Cosoli, G.; Scalise, L.; Spinsante, S.
Classificazione: 1 Contributo su Rivista
Abstract: In the field of automatic recognition and classification of Activities of Daily Living (ADLs), a paramount role to determine the classification accuracy is played by sensor technologies, as the algorithms’ performance is highly affected by the nature and quality of the collected measurement data. This work aims to investigate the influence of the wearable device characteristics and measurement uncertainty on the classification accuracy. For this study, two wearables devices are considered: a top-quality smartwatch (Empatica E4) and a low-cost Arduino-based wristband prototype. These devices have been used to measure the acceleration signal at the dominant wrist of subjects performing some relevant activities in real-life conditions. The experimental evaluation of some ADLs classification algorithms shows that their accuracy fluctuates depending on the choice of the sensor, which in turn affects the amount and type of relevant features to process. As such, the combination of features’ domain, i.e. time or frequency, number and type, which leads to the best classification accuracy has to be tuned on a specific sensor basis, despite the same type of signal, i.e. acceleration, is measured and processed under identical circumstances. Accuracy values of 50-99% and 66-95% in the ADLs classification, are obtained for Empatica E4 and Arduino-based prototype, respectively; the best performance among classifiers is obtained with J48 and Random Forest, confirming that, with an appropriate configuration, satisfactory accuracy may be attained, even by resorting to the use of simple sensors.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/283316 Collegamento a IRIS

2020 Preface to: Proceedings of the 6th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT 2019)
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Autore/i: Chlamtac, I.; Garcia, N. M.; Jevremovic, A.; Pombo, N.; Spinsante, S.
Editore: Springer
Classificazione: 2 Contributo in Volume
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/281596 Collegamento a IRIS

2020 ADLs Monitoring by Accelerometer-Based Wearable Sensors: Effect of Measurement Device and Data Uncertainty on Classification Accuracy
Proceedings of IEEE Medical Measurements and Applications Conference (MEMEA) 2020
Autore/i: Poli, Angelica; Scalise, Lorenzo; Spinsante, Susanna; Strazza, Annachiara
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/282676 Collegamento a IRIS

2020 Activities of Daily Living and Environment Recognition Using Mobile Devices: A Comparative Study
ELECTRONICS
Autore/i: Ferreira, José M.; Pires, Ivan Miguel; Marques, Gonçalo; Garcia, Nuno M.; Zdravevski, Eftim; Lameski, Petre; Flórez-Revuelta, Francisco; Spinsante, Susanna; Xu, Lina
Classificazione: 1 Contributo su Rivista
Abstract: The recognition of Activities of Daily Living (ADL) using the sensors available in off-the-shelf mobile devices with high accuracy is significant for the development of their framework. Previously, a framework that comprehends data acquisition, data processing, data cleaning, feature extraction, data fusion, and data classification was proposed. However, the results may be improved with the implementation of other methods. Similar to the initial proposal of the framework, this paper proposes the recognition of eight ADL, e.g., walking, running, standing, going upstairs, going downstairs, driving, sleeping, and watching television, and nine environments, e.g., bar, hall, kitchen, library, street, bedroom, living room, gym, and classroom, but using the Instance Based k-nearest neighbour (IBk) and AdaBoost methods as well. The primary purpose of this paper is to find the best machine learning method for ADL and environment recognition. The results obtained show that IBk and AdaBoost reported better results, with complex data than the deep neural network methods.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273137 Collegamento a IRIS

2020 Variability of muscular recruitment in hemiplegic walking assessed by EMG analysis
ELECTRONICS
Autore/i: Di Nardo, F.; Spinsante, S.; Pagliuca, C.; Poli, A.; Strazza, A.; Agostini, V.; Knaflitz, M.; Fioretti, S.
Classificazione: 1 Contributo su Rivista
Abstract: Adaptive variability during walking is typical of child motor development. It has been reported that neurological disorders could affect this physiological phenomenon. The present work is designed to assess the adaptive variability of muscular recruitment during hemiplegic walking and to detect possible changes compared to control populations. In the attempt of limiting the complexity of computational procedure, the easy-to-measure coefficient of variation (CV) index is adopted to assess surface electromyography (sEMG) variability. The target population includes 34 Winters’ type I and II hemiplegic children (H-group). Two further healthy populations, 34 age-matched children (C-group) and 34 young adults (A-group), are involved as controls. Results show a significant decrease (p < 0.05) of mean CV for gastrocnemius lateralis (GL) in H-group compared to both C-group (15% reduction) and A-group (35% reduction). Reductions of mean CV are detected also for tibialis anterior (TA) in H-group compared to C-group (7% reduction, p > 0.05) and A-group (15% reduction, p < 0.05). Lower CVs indicate a decreased intra-subject variability of ankle-muscle activity compared to controls. Novel contribution of the study is twofold: (1) To propose a CV-based approach for an easy-to-compute assessment of sEMG variability in hemiplegic children, useful in different experimental environments and different clinical purposes; (2) to provide a quantitative assessment of the reduction of intra-subject variability of ankle-muscle activity in mild-hemiplegic children compared to controls (children and adults), suggesting that hemiplegic children present a limited capability of adapting their muscle recruitment to the different stimuli met during walking task. This finding could be very useful in deepening the knowledge of this neurological disorder.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/284183 Collegamento a IRIS

2020 Identification Issues Associated with the Use of Wearable Accelerometers in Lifelogging
Human Aspects of IT for the Aged Population. Technologies, Design and User Experience. HCII 2020.
Autore/i: Poli, Angelica; Strazza, Annachiara; Cecchi, Stefania; Spinsante, Susanna
Editore: Springer, Cham
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Personal lifelogging builds upon the pervasive and continuous acquisition of sensor measurements and signals in time, and this may expose the subject, and eventually bystanders, to privacy violations. While the issue is easy to understand for image and video data, the risks associated to the use of wearable accelerometers is less clear and may be underestimated. This work addresses the problem of understanding if acceleration measurements collected from the wrist, by subjects performing different types of Activities of Daily Living (ADLs), may release personal details, for example about their gender or age. A positive outcome would motivate the need for de-identification algorithms to be applied to acceleration signals, embedded into wearable devices, in order to limit the unintentional release of personal details and ensure the necessary privacy by design and by default requirements.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/283280 Collegamento a IRIS

2020 Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review
ELECTRONICS
Autore/i: Ponciano, Vasco; Pires, Ivan Miguel; Ribeiro, Fernando Reinaldo; Marques, Gonçalo; Villasana, Maria Vanessa; Garcia, Nuno M.; Zdravevski, Eftim; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: Inertial sensors are commonly embedded in several devices, including smartphones, and other specific devices. This type of sensors may be used for different purposes, including the recognition of different diseases. Several studies are focused on the use of accelerometer signals for the automatic recognition of different diseases, and it may empower the different treatments with the use of less invasive and painful techniques for patients. This paper aims to provide a systematic review of the studies available in the literature for the automatic recognition of different diseases by exploiting accelerometer sensors. The most reliably detectable disease using accelerometer sensors, available in 54% of the analyzed studies, is the Parkinson’s disease. The machine learning methods implemented for the automatic recognition of Parkinson’s disease reported an accuracy of 94%. The recognition of other diseases is investigated in a few other papers, and it appears to be the target of further analysis in the future.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/278171 Collegamento a IRIS

2020 Sensors are Capable to Help in the Measurement of the Results of the Timed-Up and Go Test? A Systematic Review
JOURNAL OF MEDICAL SYSTEMS
Autore/i: Ponciano, Vasco; Pires, Ivan Miguel; Ribeiro, Fernando Reinaldo; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: The analysis of movements used in physiotherapy areas related to the elderly is becoming increasingly important due to factorssuch as the increase in the average life expectancy and the rate of elderly people over the whole population. In this systematic review, we try to determine how the inertial sensors embedded in mobile devices are exploited for the measurement of the different parameters involved in the Timed-Up and Go test. The results show the mobile devices equipped with onboard motion sensors can be exploited for these types of studies: the most commonly used sensors are the magnetometer, accelerometer and gyroscope available in consumer off-the-shelf smartphones. Other features typically used to evaluate the Timed-Up and Go testare the time duration, the angular velocity and the number of steps, allowing for the recognition of some diseases as well as the measurement of the subject’s performance during the test execution.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/284506 Collegamento a IRIS

2020 A Review on the Artificial Intelligence Algorithms for the Recognition of Activities of Daily Living Using Sensors in Mobile Devices
Advances in Intelligent Systems and Computing
Autore/i: Pires, I. M.; Marques, G.; Garcia, N. M.; Pombo, N.; Florez-Revuelta, F.; Zdravevski, E.; Spinsante, S.
Editore: Springer
Classificazione: 2 Contributo in Volume
Abstract: Smart environments and mobile devices are two technologies that when combined may allow the recognition of Activities of Daily Living (ADL) and its environments. This paper focuses on the literature review of the existing machine learning methods for the recognition of ADL and its environments, by means of comparison jointly with a proposal of a novel taxonomy in this context. The sensors used for this purpose depends on the nature of the system and the ADL to recognize. The available in the mobile devices are mainly motion, magnetic and location sensors, but the sensors available in the smart environments may have different types. Data acquired from several sensors can be used for the identification of ADL, where the motion, magnetic and location sensors handle the recognition of activities with movement, and the acoustic sensors handle the recognition of activities related with the environment.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/274927 Collegamento a IRIS

2020 Wrist-worn and chest-strap wearable devices: Systematic review on accuracy and metrological characteristics
MEASUREMENT
Autore/i: Cosoli, Gloria; Spinsante, Susanna; Scalise, Lorenzo
Classificazione: 1 Contributo su Rivista
Abstract: This paper analyses the state of the art on accuracy and metrological characteristics of wrist-worn and chest-strap wearable devices, in comparison with reference instruments. Basing on literature available results, neither a standard protocol for validation nor fixed metrological characteristics can be identified. Wearable devices are validated without standard procedures (test protocol, population characteristics and metrological parameters), which turns into irregular results, barely comparable each other. Therefore, it would be extremely interesting to conduct a pilot study to identify standard characteristics to evaluate accuracy, compliant to the guidelines for the expression of uncertainty in measurement and recognized by organizations promoting public health (e.g. the Food and Drug Administration in the United States). This way, it would be possible to start establishing a database of wearable devices’ metrological properties, useful not only for research, but also for caregivers and sportsmen, in different application fields (e.g. sport, medicine, Active and Assisted Living, etc.).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/276932 Collegamento a IRIS

2020 Mobile Applications Dedicated for Cardiac Patients: Research of Available Resources
Internet of Things and Big Data Applications
Autore/i: Valentim Pereira, Gonçalo F.; Pires, Ivan Miguel; Marques, Gonçalo; Garcia, Nuno M.; Zdravevski, Eftim; Lameski, Petre; Flórez-Revuelta, Francisco; Spinsante, Susanna
Editore: Springer
Luogo di pubblicazione: Cham
Classificazione: 2 Contributo in Volume
Abstract: In recent years cardiac problems and using mobile devices for aiding people with these problems have received significant attention from the scientific communities to develop solutions to improve the quality of life. The proliferation of mobile computing technologies has revolutionized the medical practices in both patient and clinical staff sides. In particular, the development of mobile health applications continues to increase; mainly, the cardiology field is the most addressed. This paper focuses on the review of the mobile applications available in the Google Play Store that are dedicated to cardiac patients. The number of cardiac patients is increasing, but there are no mobile applications that aid cardiac patients by providing monitoring of different parameters, including the calorie intake and the calories burned. However, the mobile applications that can be adapted to this type of people were analyzed. We found six notable mobile applications. Their features can be grouped in diet, anthropometric parameters, and physical activity.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/275040 Collegamento a IRIS

2020 Is The Timed-Up and Go Test Feasible in Mobile Devices? A Systematic Review
ELECTRONICS
Autore/i: Ponciano, Vasco; Pires, Ivan Miguel; Ribeiro, Fernando Reinaldo; Marques, Gonçalo; Garcia, Nuno M.; Pombo, Nuno; Spinsante, Susanna; Zdravevski, Eftim
Classificazione: 1 Contributo su Rivista
Abstract: The number of older adults is increasing worldwide, and it is expected that by 2050 over 2 billion individuals will be more than 60 years old. Older adults are exposed to numerous pathological problems such as Parkinson’s disease, amyotrophic lateral sclerosis, post-stroke, and orthopedic disturbances. Several physiotherapy methods that involve measurement of movements, such as the Timed-Up and Go test, can be done to support efficient and effective evaluation of pathological symptoms and promotion of health and well-being. In this systematic review, the authors aim to determine how the inertial sensors embedded in mobile devices are employed for the measurement of the different parameters involved in the Timed-Up and Go test. The main contribution of this paper consists of the identification of the different studies that utilize the sensors available in mobile devices for the measurement of the results of the Timed-Up and Go test. The results show that mobile devices embedded motion sensors can be used for these types of studies and the most commonly used sensors are the magnetometer, accelerometer, and gyroscope available in off-the-shelf smartphones. The features analyzed in this paper are categorized as quantitative, quantitative + statistic, dynamic balance, gait properties, state transitions, and raw statistics. These features utilize the accelerometer and gyroscope sensors and facilitate recognition of daily activities, accidents such as falling, some diseases, as well as the measurement of the subject's performance during the test execution.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/275507 Collegamento a IRIS

2020 Identification of Daily Activites and Environments Based on the AdaBoost Method Using Mobile Device Data: A Systematic Review
ELECTRONICS
Autore/i: Ferreira, José M.; Pires, Ivan Miguel; Marques, Gonçalo; Garcia, Nuno M.; Zdravevski, Eftim; Lameski, Petre; Flórez-Revuelta, Francisco; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: Using the AdaBoost method may increase the accuracy and reliability of a framework for daily activities and environment recognition. Mobile devices have several types of sensors, including motion, magnetic, and location sensors, that allow accurate identification of daily activities and environment. This paper focuses on the review of the studies that use the AdaBoost method with the sensors available in mobile devices. This research identified the research works written in English about the recognition of daily activities and environment recognition using the AdaBoost method with the data obtained from the sensors available in mobile devices that were published between 2012 and 2018. Thus, 13 studies were selected and analysed from 151 identified records in the searched databases. The results proved the reliability of the method for daily activities and environment recognition, highlighting the use of several features, including the mean, standard deviation, pitch, roll, azimuth, and median absolute deviation of the signal of motion sensors, and the mean of the signal of magnetic sensors. When reported, the analysed studies presented an accuracy higher than 80% in recognition of daily activities and environments with the Adaboost method.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273136 Collegamento a IRIS

2020 On the importance of the sound emitted by honey bee hives
VETERINARY SCIENCES
Autore/i: Terenzi, Alessandro; Cecchi, Stefania; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: Recent years have seen a worsening in the decline of honey bees (Apis mellifera L.) colonies. This phenomenon has sparked a great amount of attention regarding the need for intense bee hive monitoring, in order to identify possible causes, and design corresponding countermeasures. Honey bees have a key role in pollination services of both cultivated and spontaneous flora, and the increase in bee mortality could lead to an ecological and economical damage. Despite many smart monitoring systems for honey bees and bee hives, relying on different sensors and measured quantities, have been proposed over the years, the most promising ones are based on sound analysis. Sounds are used by the bees to communicate within the hive, and their analysis can reveal useful information to understand the colony health status and to detect sudden variations, just by using a simple microphone and an acquisition system. The work here presented aims to provide a review of the most interesting approaches proposed over the years for honey bees sound analysis and the type of knowledge about bees that can be extracted from sounds.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/285073 Collegamento a IRIS

2020 Physical Stimuli and Emotions: EDA Features Analysis from a Wrist-Worn Measurement Sensor
Proceedings of 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)
Autore/i: Cecchi, Stefania; Piersanti, Agnese; Poli, Angelica; Spinsante, Susanna
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/284050 Collegamento a IRIS

2020 Impact of the sensing device on machine learning-based recognition of human activity
Atti del IV Forum Nazionale delle Misure
Autore/i: Spinsante, S.; Poli, A.; Scalise, L.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/286034 Collegamento a IRIS

2020 A Wearable Fall Detection System based on LoRa LPWAN Technology
JOURNAL OF COMMUNICATIONS SOFTWARE AND SYSTEMS
Autore/i: Zanaj, Elma; Disha, Deivis; Spinsante, Susanna; Gambi, Ennio
Classificazione: 1 Contributo su Rivista
Abstract: Several technological solutions now available in the market offer the possibility of increasing the independent life of people who by age or pathologies otherwise need assistance. In particular, internet-connected wearable solutions are of considerable interest, as they allow continuous monitoring of the user. However, their use poses different challenges, from the real usability of a device that must still be worn to the performance achievable in terms of radio connectivity and battery life. The acceptability of a technology solution, by a user who would still benefit from its use, is in fact often conditioned by practical problems that impact the person’s normal lifestyle. The technological choices adopted in fact strongly determine the success of the proposed solution, as they may imply limitations both to the person who uses it and to the achievable performance. In this document, targeting the case of a fall detection sensor based on a pair of sensorized shoes, the effectiveness of a real implementation of an Internet of Things technology is examined. It is shown how alarming events, generated in a metropolitan context, are effectively sent to a supervision system through Low Power Wide Area Network technology without the need for a portable gateway. The experimental results demonstrate the effectiveness of the chosen technology, which allows the user to take advantage of the support of a wearable sensor without being forced to substantially change his lifestyle.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/285693 Collegamento a IRIS

2020 A review on video-based active and assisted living technologies for automated lifelogging
EXPERT SYSTEMS WITH APPLICATIONS
Autore/i: Climent-Pérez, Pau; Spinsante, Susanna; Mihailidis, Alex; Florez-Revuelta, Francisco
Classificazione: 1 Contributo su Rivista
Abstract: Providing support for ageing and frail populations to extend their personal autonomy is desirable for their well-being as it is for the society at large, since it can ease the economic and social challenges caused by ever-ageing developed societies. Ambient-assisted living (AAL) technologies and services might be a solution to address those challenges. Recent improved capabilities in both ambient and wearable technologies, especially those related with video and lifelogging data, and huge advances in the accuracy of intelligent systems for AAL are leading to more valuable and trustworthy services for older people and their caregivers. These advances have been particularly relevant in the last years due to the appearance of RGB-D devices and the development of deep learning systems. This article reviews these latest developments in the intersection of AAL, intelligent systems, lifelogging, and computer vision. This paper provides a study of previous reviews in these fields, and later analyses newer intelligent techniques employed with different video-based lifelogging technologies in order to offer lifelogging services for AAL. Additionally, privacy and ethical issues associated with these technologies are discussed. This review aims at facilitating the understanding of the multiple fields involved.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269313 Collegamento a IRIS

2020 A field-measurements-based LoRa network planning tool
ACTA IMEKO
Autore/i: Spinsante, Susanna; Gioacchini, Luca; Scalise, Lorenzo
Classificazione: 1 Contributo su Rivista
Abstract: Long range (LoRa) transmission technology enables energy-constrained devices such as the tiny sensor systems used in internet-of-things applications that are distributed over wide areas while still being able to establish appropriate connectivity. This has resulted in the development of an exponentially increasing number of different solutions and services based on LoRa, be they dedicated to the long-term monitoring of distributed plants and infrastructures or to human-centred applications such as safety-oriented sensor systems for use in the workplace. In dense LoRa networks, predicting the number of supported nodes in relation to their position and the propagation environment is essential for ensuring reliable and stable communication and minimising costs. In this paper, after comparing different path loss models based on a field measurement campaign for LoRa received signal strength indicator values within a university campus, two main modifications of the LoRa simulator tool were implemented. These were aimed at improving the accuracy of the prediction of the number of sustainable nodes in relation to the target data extraction rate set. The simulations based on field measurements demonstrated that through an improved path loss evaluation and the use of three gateways, the number of nodes could be increased theoretically from around 100 to around 6,000.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/286035 Collegamento a IRIS

2020 Hybridized-GNSS Approaches to Train Positioning: Challenges and Open Issues on Uncertainty
SENSORS
Autore/i: Spinsante, Susanna; Stallo, Cosimo
Classificazione: 1 Contributo su Rivista
Abstract: In recent years, the development of advanced systems and applications has propelled the adoption of autonomous railway traffic and train positioning, with several ongoing initiatives and experimental testbeds aimed at proving the suitability and reliability of the Global Navigation Satellite System signals and services, in this specific application domain. To satisfy the strict safety and accuracy requirements aimed at assuring the position solution's integrity, availability, accuracy and reliability, recent proposals suggest the hybridization of the Global Navigation Satellite System with other technologies. The integration with localization techniques that are expected to be available with the upcoming fifth generation mobile communication networks is among the most promising approaches. In this work, different approaches to the design of hybrid positioning solutions for the railway sector are examined, under the perspective of the uncertainty evaluation of the attained results and performance. In fact, the way the uncertainty associated to the positioning measurements performed by different studies is reported is often not consistent with the Guide to the Expression of Uncertainty in Measurement, and this makes it very difficult to fairly compare the different approaches in order to identify the best emerging solution. Under this perspective, the review provided by this work highlights a number of open issues that should drive future research activities in this field.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/275761 Collegamento a IRIS

2020 A smart sensor-based measurement system for advanced bee hive monitoring
SENSORS
Autore/i: Cecchi, S.; Spinsante, S.; Terenzi, A.; Orcioni, S.
Classificazione: 1 Contributo su Rivista
Abstract: The widespread decline of honey bee (Apis mellifera L.) colonies registered in recent years has raised great attention to the need of gathering deeper knowledge about this phenomenon, by observing the colonies’ activity to identify possible causes, and design corresponding countermeasures. In fact, honey bees have well-known positive effects on both the environment and human life, and their preservation becomes critical not only for ecological reasons, but also for the social and economic development of rural communities. Smart sensor systems are being developed for real-time and long-term measurement of relevant parameters related to beehive conditions, such as the hive weight, sounds emitted by the bees, temperature, humidity, and CO2 inside the beehive, as well as weather conditions outside. This paper presents a multisensor platform designed to measure the aforementioned parameters from beehives deployed in the field, and shows how the fusion of different sensor measurements may provide insights on the status of the colony, its interaction with the surrounding environment, and the influence of climatic conditions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/281591 Collegamento a IRIS

2019 The Role of Mobile Apps in Heart Rate Measurement with Consumer Devices
Proceedings of the 2019 IEEE 23rd INTERNATIONAL SYMPOSIUM ON CONSUMER TECHNOLOGIES
Autore/i: Spinsante, Susanna; Valeria, Cerquetti; Poli, Angelica; Scalise, Lorenzo
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/267654 Collegamento a IRIS

2019 Smartphone-based automatic measurement of the results of the Timed-Up and Go test
Proceedings of 5th EAI International Conference on Smart Objects and Technologies for Social Good (GoodTechs ’19)
Autore/i: Ponciano, Vasco; Pires, Ivan Miguel; Ribeiro, Fernando Reinaldo; Garcia, Nuno M.; Pombo, Nuno; Spinsante, Susanna; Crisóstomo, Rute
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269350 Collegamento a IRIS

2019 A novel approach for measuring treeline spatial complexity
1st Workshop on Metrology for Agriculture and Forestry, METROAGRIFOR 2018
Autore/i: Spinsante, S.; Montalto, L.; Garbarino, M.; Malandra, F.; Weisberg, P. J.; Paone, N.; Scalise, L.
Editore: Institute of Physics Publishing
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Treelines, defined as ecotonal zones between closed forest and the uppermost trees, are particularly sensitive to global changes related to climate and anthropic activities. Different mechanisms of treeline formation can be detected as subtle differences in ecotonal structure, which in turn have important implications for how treelines function and potentially respond to global changes. So, it is of interest to be able to measure in a precise and quantitative way treelines' properties reflecting climate and land use changes. Classical tools adopted to measure treeline spatial patterns are not able to fully understand the limiting factors affecting them. This work presents a novel textural analysis of treeline spatial structure based on the measurement of surface roughness, and applies the corresponding metrics to twenty study areas at both Upper and Lower treelines, where all tree crowns have been mapped at high precision. Preliminary results are promising and motivate future and more extensive evaluations on bigger datasets.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/266629 Collegamento a IRIS

2019 Integrated Consumer Technologies for Older Adults' Quality of Life Improvement: the vINCI Project
Proceedings of the 2019 IEEE 23rd INTERNATIONAL SYMPOSIUM ON CONSUMER TECHNOLOGIES
Autore/i: SPINSANTE, Susanna; STRAZZA, ANNACHIARA; Dobre, Ciprian; Bajenaru, Lidia; Mavromoustakis, Constandinos X.; Mongay Batalla, Jordi; Krawiec, Piotr; Georgescu, George; Molan, Gregor; Gonzalez-Velez, Horacio; Marie Herghelegiu, Anna; Ioan Prada, Gabriel; Draghici, Rozeta
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/267655 Collegamento a IRIS

2019 RGB-D Sensors and Signal Processing for Fall Detection
RGB-D Image Analysis and Processing
Autore/i: Spinsante, Susanna
Editore: Springer, Cham
Classificazione: 2 Contributo in Volume
Abstract: Globally, falls are a major public health problem, and an important cause of morbidity and mortality in the older population. As such, fall detection is one of the most important application areas within the framework of Ambient-Assisted Living (AAL) solutions. Studies report that the majority of falls occur at home, as a person’s living environment is filled with potential hazards, predominantly in the living room and in the bedroom. In addition, recent studies report that fall kinematics varies depending on the weight and size of the falling person, and that most people fall in the evening or during the night. All these features may be captured by RGB-D sensors properly installed in the environment, and detected by suitable processing of the signals generated by the sensors themselves. Fall detection based on RGB-D signal processing has gained momentum in the past years, thanks to the availability of easy-to-use sensors that are able to provide not only raw RGB-D signals but also preprocessed data like joints and skeleton spatial coordinates; additionally, depth signal processing allows to maintain adequate privacy in human monitoring, especially at the levels deemed acceptable by monitored subjects in their own home premises. This chapter will first provide an overview of the RGB-D sensors mostly used in fall detection applications, by discussing their main properties and the modalities by which they have been used and installed. Then, the most relevant signal processing approaches aimed at fall detection will be presented and analyzed, together with an overview of their performances, advantages and limitations, as discussed and presented in the most relevant and up-to-date literature. The aim of the chapter is to provide the reader with a basic understanding of what is reasonably expectable, in terms of detection capability, from RGB-D sensors, applied to fall detection; what are the main depth signal processing approaches according to the sensor usage, and what type of information can be extracted from them.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/271273 Collegamento a IRIS

2019 Multi-sensor platform for real time measurements of honey bee hive parameters
IOP Conference Series: Earth and Environmental Science
Autore/i: Cecchi, S.; Terenzi, A.; Orcioni, S.; Spinsante, S.; Mariani Primiani, V.; Moglie, F.; Ruschioni, S.; Mattei, S.; Riolo, P.; Isidoro, N.
Editore: Institute of Physics Publishing
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/266895 Collegamento a IRIS

2019 OPENCARE: Emergent Technologies for the Care of Older Adults in Residential Facilities
Lecture Notes in Electrical Engineering
Autore/i: Stara, Vera; Spinsante, Susanna; Olivetti, Paolo; Rossi, Lorena; Montanini, Laura; Gambi, Ennio; Ciattaglia, Gianluca
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/263827 Collegamento a IRIS

2019 A Software Tool for Quick Codes Analysis and Selection in Spread Spectrum Communication Systems
ELECTRICAL & COMPUTER ENGINEERING
Autore/i: Sarayloo, Mahdiyar; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: Spread spectrum communications rely on the selection of suitable sets of so-called spreading codes, also known as signatures, to ensure satisfactory system performance. Comparing different sets of spreading codes may be not a straightforward process, due to the amount of different code-related parameters that should be taken into account, and to the inherent differences in the codes generation algorithms. This paper presents a practical software tool to facilitate the evaluation and comparison of different families of spreading codes, under different parameters and constraints. Simulations to evaluate the selected signatures in a CDMA system, under AWGN or multipath channel, are also supported by the tool. The tool may be usefully applied in the design of communication systems and networks relying upon spread spectrum techniques.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259175 Collegamento a IRIS

2019 Accuracy of Heart Rate Measurements by a Smartwatch in Low Intensity Activities
Proceedings of the 2019 IEEE International Symposium on Medical Measurements & Applications (MeMeA)
Autore/i: SPINSANTE, Susanna; Porfiri, Sara; SCALISE, Lorenzo
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265004 Collegamento a IRIS

2019 A Simple sEMG-Based Measure of Muscular Recruitment Variability During Pediatric Walking
Proceedings of the 2019 IEEE International Symposium on Medical Measurements & Applications (MeMeA)
Autore/i: SPINSANTE, Susanna; DI NARDO, Francesco; STRAZZA, ANNACHIARA; VERDINI, Federica; POLI, ANGELICA
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265005 Collegamento a IRIS

2019 A novel experimental-based tool for the design of LoRa networks
Proceedings of the 2019 IEEE International Workshop on Metrology for Industry 4.0 and IoT
Autore/i: Spinsante, Susanna; Gioacchini, Luca; Scalise, Lorenzo
Editore: IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265006 Collegamento a IRIS

2019 Recognition of Activities of Daily Living and Environments Using Acoustic Sensors Embedded on Mobile Devices
ELECTRONICS
Autore/i: Pires, Ivan Miguel; Marques, Gonçalo; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna; Teixeira, Maria Canavarro; Zdravevski, Eftim
Classificazione: 1 Contributo su Rivista
Abstract: The identification of Activities of Daily Living (ADL) is intrinsic with the user’s environment recognition. This detection can be executed through standard sensors present in every-day mobile devices. On the one hand, the main proposal is to recognize users’ environment and standing activities. On the other hand, these features are included in a framework for the ADL and environment identification. Therefore, this paper is divided into two parts—firstly, acoustic sensors are used for the collection of data towards the recognition of the environment and, secondly, the information of the environment recognized is fused with the information gathered by motion and magnetic sensors. The environment and ADL recognition are performed by pattern recognition techniques that aim for the development of a system, including data collection, processing, fusion and classification procedures. These classification techniques include distinctive types of Artificial Neural Networks (ANN), analyzing various implementations of ANN and choosing the most suitable for further inclusion in the following different stages of the developed system. The results present 85.89% accuracy using Deep Neural Networks (DNN) with normalized data for the ADL recognition and 86.50% accuracy using Feedforward Neural Networks (FNN) with non-normalized data for environment recognition. Furthermore, the tests conducted present 100% accuracy for standing activities recognition using DNN with normalized data, which is the most suited for the intended purpose.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272494 Collegamento a IRIS

2019 Development of a wireless system able to track barbell kinematics during bench-press, deadlift and squat movements
Medical Measurements and Applications, MeMeA 2019 - Symposium Proceedings
Autore/i: Ricciardi, L.; Innocenti, B.; Spinsante, S.; Scalise, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The monitoring of sport activity during the execution of different exercises plays an important role, not only for athletes of high level. The aim of this present study was to build a system able to acquire kinematics data (acceleration and displacement) of the barbell, in a wireless and real time fashion, during the execution of squat, deadlift and bench-press movements. At first, the hardware components were evaluated to obtain a cheap and light system, then an algorithm for the determination of displacement of the barbell from acceleration and angular velocity was developed; to conclude, tests, both in ideal and real conditions, were performed. The acceleration signals obtained for squat and deadlift were really noisy, so it was not possible to determine the displacement because of drift phenomenon. The accelerations obtained during bench-press showed better results and allowed the determination of displacement with an uncertainty of ± 30 cm. The study showed that in uncontrolled conditions, due to the noise, this system is not able to determine the amplitude of the displacement, while in conditions similar to the ideal, as in bench-press, the system is able to determine the displacement though with a low level of accuracy.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/270880 Collegamento a IRIS

2019 Real-time System Implementation for Bee Hives Weight Measurement
2019 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor 2019) Proceedings
Autore/i: Terenzi, A.; Cecchi, S.; Spinsante, S.; Orcioni, S.; Piazza, F.
Editore: IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/271119 Collegamento a IRIS

2019 Micro Doppler Radar and Depth Sensor Fusion for Human Monitoring in AAL
4th National Conference on Sensors
Autore/i: Spinsante, S.; Pepa, M.; Pirani, S.; Gambi, E.; Fioranelli, F.
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/254477 Collegamento a IRIS

2019 Issues on Uncertainty to Train Positioning in Hybridized-GNSS Approaches
Proceedings of the 2019 IEEE International Workshop on Metrology for Aerospace
Autore/i: Spinsante, Susanna; Stallo, Cosimo
Editore: IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265371 Collegamento a IRIS

2019 Enanced video heart rate and respiratory rate evaluation: Standard multiparameter monitor vs clinical confrontation in newborn patients
Medical Measurements and Applications, MeMeA 2019 - Symposium Proceedings
Autore/i: Antognoli, Luca; Marchionni, Paolo; Spinsante, S.; Nobile, S.; Carnielli, V. P.; Scalise, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Vital signs in neonatal care are usually measured by a multiparameter monitor (MM). However, this kind of device is inaccurate on the assessment in newborns, which can present different respiratory patterns and superficial breathing, resulting hardly detectable by the MM. In some cases, the assessment of the physician is more effective on the evaluation of the patient. In this paper we present a non-contact solution to measure the respiration rate (RR) and heart rate (HR) using a commercially available web-camera (WeC) and a personal computer (PC). We use Eulerian Video Magnification (EVM) to amplify the color variations in the image sequence. By extracting the signal from the thorax portion of the patients we are able to measure the RR and HR by spectral analysis. The results are compared with the MM and the assessment of the physician. The measures of RR and HR correlate with the data from the MM and result even more accurate than the MM when compared with the physician's evaluation. We collect data on 40 patients demonstrating the feasibility of this method. The measure of RR and HR shows a root mean square error of 6.8 bpm for the HR and 2.1 bpm for the RR.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/270881 Collegamento a IRIS

2019 Assistive sensor-based technology driven self-management for building resilience among people with early stage cognitive impairment
2019 IEEE International Symposium on Measurements and Networking, M and N 2019 - Proceedings
Autore/i: Casaccia, S.; Bevilacqua, R.; Scalise, L.; Revel, G. M.; Astell, A. J.; Spinsante, S.; Rossi, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This paper reports the technologies and workplan of the AAL RESILIEN-T project. Focused on assistive technologies, RESILIEN-T aims to improve, through self-management, the autonomy, participation in social life, and skills, of older Persons with Cognitive Impairment (PwCI) who are too often considered as “objects” of research, rather than “partners”. The study investigates existing ICT solutions to improve the self-management ability of PwCl at different stages of cognitive impairment. Sensors, devices and apps to reduce the progression of the disease are analyzed. To increase sensor capability, innovative data management, i.e. Artificial Intelligence and Machine Learning algorithms, are considered to extract significant information from the data and optimize the sensor network. Moreover, approaches to involve end-users in the development are also investigated to enhance the final outputs. The study proposes a modular and integrated platform for PwCI to self-manage various activities including nutrition, physical activities, social life, cognitive training. The choice of offering an open API to integrate wearable devices and lifestyle monitoring systems from different suppliers makes available a customable and modular product. Considering that functional decline is part of the normal aging process, it might be challenging to individuate three levels of modular architecture to increase the accuracy of the monitoring with the decline of the cognitive capabilities.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/270879 Collegamento a IRIS

2019 Acceptability of Digital Quality of Life Questionnaire Corroborated with Data from Tracking Devices
Proceedings of 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)
Autore/i: Draghici, Rozeta; Rusu, Alexandra; Prada, Gabriel Ioan; Herghelegiu, Anna Marie; Bajenaru, Lidia; Dobre, Ciprian; Mavromoustakis, Constandinos X.; Spinsante, Susanna; Batalla, Jordi Mongay; Gonzalez-Velez, Horacio
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/270856 Collegamento a IRIS

2019 Improving the Collection and Understanding the Quality of Datasets for the Aim of Human Activity Recognition
Smart Assisted Living
Autore/i: Poli, Angelica; Spinsante, Susanna; Nugent, Chris; Cleland, Ian
Editore: Springer
Luogo di pubblicazione: Cham
Classificazione: 2 Contributo in Volume
Abstract: In the last few decades, life expectancy has been increasing. This has resulted in a higher proportion of older adults and increased prevalence of chronic conditions, posing challenges facing care needs. A possible solution is to foster both the prevention and health-related re-education, supporting healthier lifestyle and facilitating independent living. To facilitate this, it is crucial to measure individual’s key health metrics. For instance, human activity recognition through sensors provides valuable information about an individual’s lifestyle. Some crucial decisions, among which the quality of data collection, strengthen the methodological approach. This chapter addresses how the quality of data may affect the recognition performance. Two datasets of daily activities were collected through a triaxial accelerometer placed on the subject’s dominant wrist. The first dataset was collected by 141 users, whereas the second one comprised semi-realistic activities executed by three individuals. Specifically, outcomes were based on a comparison of activity recognition performance of six machine learning classifiers. Results show that, firstly, a higher number of features may not improve the recognition rate. Secondly, one approach may be robust in a laboratory setting but not generalizable to real-world applications. Finally, a great variability may increase the generalization of classifiers for successful activity recognition.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269429 Collegamento a IRIS

2019 Digital Signal Processing for Audio Applications: Then, Now and the Future
The First Outstanding 50 Years of “Università Politecnica delle Marche”
Autore/i: Piazza, Francesco; Squartini, Stefano; Cecchi, Stefania; Fiori, Simone; Orcioni, Simone; Spinsante, Susanna; Pirani, Stefano
Editore: Springer
Classificazione: 2 Contributo in Volume
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272643 Collegamento a IRIS

2019 LoRa Evaluation in Mobility Conditions for a Connected Smart Shoe Measuring Physical Activity
Proceedings of the 5th IEEE International Symposium on Measurements and Networking (M&N 2019)
Autore/i: Spinsante, Susanna; Poli, Angelica; Pirani, Stefano; Gioacchini, Luca
Editore: IEEE I&M Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/267656 Collegamento a IRIS

2018 Sensitivity of the Contactless Videoplethysmography-Based Heart Rate Detection to Different Measurement Conditions
Proceedings of the 26th European Signal Processing Conference (EUSIPCO)
Autore/i: Gambi, Ennio; Ricciuti, Manola; Spinsante, Susanna
Editore: IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259765 Collegamento a IRIS

2018 Smartphone as unobtrusive sensor for real-time sleep recognition
2018 IEEE International Conference on Consumer Electronics (ICCE)
Autore/i: Montanini, Laura; Sabino, Nicola; Spinsante, Susanna; Gambi, Ennio
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Sleep is fundamental to health, performance and well-being. Studies demonstrate that, in some countries, sleep disorders are reaching epidemic levels. For this reason, automatic sleep recognition systems can be helpful, on the one hand, to foster self awareness of own habits and, on the other, to implement environment management policies to encourage sleep. In this context, we propose an unobtrusive smartphone application which relies on contextual and usage information to infer sleep habits in real-time. We test selected features using kNearest Neighbors, Decision Tree, Random Forest, and Support Vector Machine classifiers. Moreover, we exploit a 1st-order Markov Chain to improve the algorithm's performance. Experimental results demonstrate the effectiveness of the proposed approach, achieving acceptable results in term of Precision, Recall, and F1-score.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259564 Collegamento a IRIS

2018 Depth-Based Fall Detection: Outcomes from a Real Life Pilot
Atti del 9° Forum Italiano Ambient Assisted Living
Autore/i: Spinsante, Susanna; Fagiani, Marco; Severini, Marco; Squartini, Stefano; Ellmenreich, Friedrich; Martelli, Giusy
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: With the increasing ageing population representing a challenge for society and health care systems, solutions based on ICT to prolong the independent living of older adults become critical. Among them, systems able to automatically detect falls are being investigated since several years, because many solutions that appear promising when tested in lab settings, fail when faced with the constraints and unforeseen circumstances of real deployments. In this paper, we present the outcomes resulting from the pilot installation of a fall detection system based on the use of depth sensors located on the ceiling of the monitored apartment, where a 75 years old woman lives alone. We highlight the system design process, moving from the research leading to an original algorithm working offline, preliminarily tested in a lab setting, to the real-time engineering of the software, and the physical deployment of the system. Testing the system in a real-life scenario allowed us to identify a number of tricks and conditions that should to be taken into account since the initial steps, but the lab experimentation alone can barely help to focus on.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259009 Collegamento a IRIS

2018 Android Library for Recognition of Activities of Daily Living: Implementation Considerations, Challenges, and Solutions
THE OPEN BIOINFORMATICS JOURNAL
Autore/i: Pires, Ivan Miguel; Teixeira, Maria Canavarro; Pombo, Nuno; Garcia, Nuno M.; Flórez-Revuelta, Francisco; Spinsante, Susanna; Goleva, Rossitza; Zdravevski, Eftim
Classificazione: 1 Contributo su Rivista
Abstract: Background: Off-the-shelf-mobile devices have several sensors available onboard that may be used for the recognition of Activities of Daily Living (ADL) and the environments where they are performed. This research is focused on the development of Ambient Assisted Living (AAL) systems, using mobile devices for the acquisition of the different types of data related to the physical and physiological conditions of the subjects and the environments. Mobile devices with the Android Operating Systems are the least expensive and exhibit the biggest market while providing a variety of models and onboard sensors. Objective: This paper describes the implementation considerations, challenges and solutions about a framework for the recognition of ADL and the environments, provided as an Android library. The framework is a function of the number of sensors available in different mobile devices and utilizes a variety of activity recognition algorithms to provide a rapid feedback to the user. Methods: The Android library includes data fusion, data processing, features engineering and classification methods. The sensors that may be used are the accelerometer, the gyroscope, the magnetometer, the Global Positioning System (GPS) receiver and the microphone. The data processing includes the application of data cleaning methods and the extraction of features, which are used with Deep Neural Networks (DNN) for the classification of ADL and environment. Throughout this work, the limitations of the mobile devices were explored and their effects have been minimized. Results: The implementation of the Android library reported an overall accuracy between 58.02% and 89.15%, depending on the number of sensors used and the number of ADL and environments recognized. Compared with the results available in the literature, the performance of the library reported a mean improvement of 2.93%, and they do not differ at the maximum found in prior work, that based on the Student’s t-test. Conclusion: This study proves that ADL like walking, going upstairs and downstairs, running, watching TV, driving, sleeping and standing activities, and the bedroom, cooking/kitchen, gym, classroom, hall, living room, bar, library and street environments may be recognized with the sensors available in off-the-shelf mobile devices. Finally, these results may act as a preliminary research for the development of a personal digital life coach with a multi-sensor mobile device commonly used daily.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259170 Collegamento a IRIS

2018 Identification of activities of daily living through data fusion on motion and magnetic sensors embedded on mobile devices
PERVASIVE AND MOBILE COMPUTING
Autore/i: Pires, Ivan Miguel; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna; Teixeira, Maria Canavarro
Classificazione: 1 Contributo su Rivista
Abstract: Several types of sensors have been available in off-the-shelf mobile devices, including motion, magnetic, vision, acoustic, and location sensors. This paper focuses on the fusion of the data acquired from motion and magnetic sensors, i.e., accelerometer, gyroscope and magnetometer sensors, for the recognition of Activities of Daily Living (ADL). Based on pattern recognition techniques, the system developed in this study includes data acquisition, data processing, data fusion, and classification methods like Artificial Neural Networks (ANN). Multiple settings of the ANN were implemented and evaluated in which the best accuracy obtained, with Deep Neural Networks (DNN), was 89.51%. This novel approach applies L2 regularization and normalization techniques on the sensors’ data proved it suitability and reliability for the ADL recognition.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258875 Collegamento a IRIS

2018 Contactless Measurement of Heart Rate for Exergames Applications
Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications
Autore/i: Spinsante, Susanna; Ricciuti, Manola; Scalise, Lorenzo
Editore: IEEE I&M Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258884 Collegamento a IRIS

2018 PRBS Selection for Velocity Measurements with Compressive Sampling-Based DS-CDMA Radio Navigation Receivers
Proceedings of the 5th IEEE International Workshop on Metrology for Aerospace, 2018
Autore/i: Daponte, Pasquale; De Vito, Luca; Iadarola, Grazia; Spinsante, Susanna
Editore: IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258886 Collegamento a IRIS

2018 Measurement of Elderly Daily Physical Activity by Unobtrusive Instrumented Shoes
Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications
Autore/i: Spinsante, Susanna; Scalise, Lorenzo
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258885 Collegamento a IRIS

2018 Fall Detection with Kinect in Top View: Preliminary Features Analysis and Characterization
Smart Objects and Technologies for Social Good. GOODTECHS 2017
Autore/i: Spinsante, Susanna; Ricciuti, Manola; Cippitelli, Enea; Gambi, Ennio
Editore: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 233. Springer, Cham
Classificazione: 2 Contributo in Volume
Abstract: Fall detection is a well investigated research area, for which different solutions have been designed, based on wearable or ambient sensors. Depth sensors, like Kinect, located in front view with respect to the monitored subject, are able to provide the human skeleton through the automatic identification of body joints, and are typically used for their unobtrusiveness and inherent privacy-preserving capability. This paper aims to analyze depth signals captured from a Kinect used in top view, to extract useful features for the automatic identification of falls, despite the unavailability of joints and skeleton data. This study, based on a set of signals captured over a number of test users performing different types of falls and activities, shows that the speed of falling computed over the blob identifying the person, extracted from the depth images, should be used as a feature to spot fall events in conjunction with other metrics, for a better reliability.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255080 Collegamento a IRIS

2018 IoT-Enabled Smart Gas and Water Grids: from Communication Protocols to Data Analysis
Internet of Things: Challenges, Advances, and Applications
Autore/i: Susanna, Spinsante; Stefano, Squartini; Paola, Russo; Adelmo De Santis, ; Marco, Severini; Marco, Fagiani; Valentina Di Mattia, ; Roberto, Minerva
Editore: Chapman and Hall / CRC Computer and Information Science Series
Classificazione: 2 Contributo in Volume
Abstract: Internet of Things (IoT) has become an enabling technology in a huge number of diverse domains, including smart manufacturing, health, and cities. The latter encompasses cyber-physical infrastructures able to improve the citizens’ quality of life in a broader sense, including so-called smart grids (for water, natural gas, energy delivery). This chapter highlights the challenges and possible solutions related to the IoT-oriented design and deployment of smart water and gas grids, and unveils the potentially disruptive impact data analytics and machine learning could have in their management, and in consumption forecasting. The chapter reviews both capillary networks, and future opportunities provided by cellular IoT, as communication infrastructures. Open issues in network planning for smart metering applications, from an electromagnetic perspective, are also discussed, and supported by experimental evaluations. A thorough review of the state-of-the-art literature in the field of machine learning for leakage detection and consumption forecasting concludes the chapter.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252825 Collegamento a IRIS

2018 A footwear-based methodology for fall detection
IEEE SENSORS JOURNAL
Autore/i: Montanini, Laura; Del Campo, Antonio; Perla, Davide; Spinsante, Susanna; Gambi, Ennio
Classificazione: 1 Contributo su Rivista
Abstract: Automatic fall detection is an active research area since several years. Basically, this is motivated by the impact that falls have, in terms of mortality, morbidity, and social costs, which make them comparable to road traffic injuries. The early detection of a fall can be critical to reduce the mortality rate and to limit the associated health consequences. Technological solutions designed to automatically detect and notify a fall may be classified into wearable and non-wearable. Among the former ones, the use of specific devices to be worn by the subject is a very common assumption, but it fails to address user’s acceptability issues. In fact, the position of the sensor or its visibility may be perceived as a stigma associated with the primary function of fall detection. To address such an issue, this paper presents a methodology for fall detection that relies on a pair of smart shoes, equipped with force sensors and a tri-axial accelerometer, able to detect a fall and notify it to a supervising system. The instrumented footwear enables the analysis of the subject’s motion and foot orientation, recognizing abnormal configurations. The developed algorithm is not computationally intensive, and therefore can be easily executed on board the wearable device. Laboratory tests provided satisfactory performances in falls detection and correct classification: on 544 falls and 136 activities of daily living, performed by 17 healthy subjects, a 97.1% accuracy has been achieved. Further experiments involving two elderly users demonstrate the effectiveness of the proposed method in a real-life scenario.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252197 Collegamento a IRIS

2018 Guest Editorial: Computer vision in healthcare and assisted living
IET COMPUTER VISION
Autore/i: Flórez-Revuelta, Francisco; Chaaraoui, Alexandros Andre; Makris, Dimitrios; Mirmehdi, Majid; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253652 Collegamento a IRIS

2018 Privacy-Aware and Acceptable Lifelogging services for older and frail people: the PAAL project
Proceedings of 2018 IEEE 8th International Conference on Consumer Electronics - Berlin (ICCE-Berlin)
Autore/i: Florez-Revuelta, Francisco; Mihailidis, Alex; Ziefle, Martina; Colonna, Liane; Spinsante, Susanna
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259664 Collegamento a IRIS

2018 A home automation architecture based on LoRa technology and Message Queue Telemetry Transfer protocol
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
Autore/i: Gambi, Ennio; Montanini, Laura; Pigini, Danny; Ciattaglia, Gianluca; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: In recent years, Internet of Things technologies gained momentum in various application areas, including the Smart Home field. In this view, the smart objects available in the house can communicate with each other and with the outside world by adopting solutions already proposed for Internet of Things. In fact, among the challenges to face during the design and implementation of an Internet of Things–based Smart Home infrastructure, battery usage represents a key point for the realization of an efficient solution. In this context, the communication technology chosen plays a fundamental role, since transmission is generally the most energy demanding task, and Internet of Things communication technologies are designed to reduce as much as possible the power consumption. This article describes an Internet of Things-oriented architecture for the Smart Home, based on the long-range and low-power technology LoRa. Moreover, in order to enable the devices to communicate with each other and the outside world, the Message Queue Telemetry Transfer protocol is used as a domotic middleware. We show that LoRa, designed by having in mind the typical requirements of Internet of Things (i.e. low power consumption, sporadic transmission, and robustness to interference), is well-suited to also meet the need of more established home automation systems, specifically the low latency in message delivery. Interoperability among different devices may also be obtained through the Message Queue Telemetry Transfer midlleware.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/261194 Collegamento a IRIS

2018 Recognition of activities of daily living based on environmental analyses using audio fingerprinting techniques: A systematic review
SENSORS
Autore/i: Pires, Ivan Miguel; Santos, Rui; Pombo, Nuno; Nuno M., Garcia; Flórez-Revuelta, Francisco; Spinsante, Susanna; Goleva, Rossitza; Zdravevski, Eftim
Classificazione: 1 Contributo su Rivista
Abstract: An increase in the accuracy of identification of Activities of Daily Living (ADL) is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL) tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices. A comprehensive literature search was conducted in order to identify relevant English language works aimed at the identification of the environment of ADLs using data acquired with mobile devices, published between 2002 and 2017. In total, 40 studies were analyzed and selected from 115 citations. The results highlight several audio fingerprinting techniques, including Modified discrete cosine transform (MDCT), Mel-frequency cepstrum coefficients (MFCC), Principal Component Analysis (PCA), Fast Fourier Transform (FFT), Gaussian mixture models (GMM), likelihood estimation, logarithmic moduled complex lapped transform (LMCLT), support vector machine (SVM), constant Q transform (CQT), symmetric pairwise boosting (SPB), Philips robust hash (PRH), linear discriminant analysis (LDA) and discrete cosine transform (DCT).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252586 Collegamento a IRIS

2018 Approach for the Development of a Framework for the Identification of Activities of Daily Living Using Sensors in Mobile Devices
SENSORS
Autore/i: Pires, Ivan; Garcia, Nuno; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking into account several concepts, including data acquisition, data processing, data fusion, and pattern recognition. These concepts can be mapped onto different modules of the framework. The proposed framework should perform the identification of ADL without Internet connection, performing these tasks locally on the mobile device, taking in account the hardware and software limitations of these devices. The main purpose of this paper is to present a new approach for the creation of a framework for the recognition of ADL, analyzing the allowed sensors available in the mobile devices, and the existing methods available in the literature.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253925 Collegamento a IRIS

2018 Accurate fall detection in a top view privacy preserving configuration
SENSORS
Autore/i: Ricciuti, Manola; Spinsante, Susanna; Gambi, Ennio
Classificazione: 1 Contributo su Rivista
Abstract: Fall detection is one of the most investigated themes in the research on assistive solutions for aged people. In particular, a false-alarm-free discrimination between falls and non-falls is indispensable, especially to assist elderly people living alone. Current technological solutions designed to monitor several types of activities in indoor environments can guarantee absolute privacy to the people that decide to rely on them. Devices integrating RGB and depth cameras, such as the Microsoft Kinect, can ensure privacy and anonymity, since the depth information is considered to extract only meaningful information from video streams. In this paper, we propose an accurate fall detection method investigating the depth frames of the human body using a single device in a top-view configuration, with the subjects located under the device inside a room. Features extracted from depth frames train a classifier based on a binary support vector machine learning algorithm. The dataset includes 32 falls and 8 activities considered for comparison, for a total of 800 sequences performed by 20 adults. The system showed an accuracy of 98.6% and only one false positive.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258874 Collegamento a IRIS

2017 Technology-based assistance of people with dementia: state of the art, open challenges, and future developments
Human Monitoring, Smart Health and Assisted Living: Techniques and technologies
Autore/i: Susanna, Spinsante; Ennio, Gambi; Laura, Raffaeli; Laura, Montanini; Luca, Paciello; Roberta, Bevilacqua; Carlos, Chiatti; Lorena, Rossi
Editore: Institution of Engineering and Technology
Classificazione: 2 Contributo in Volume
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250003 Collegamento a IRIS

2017 Human Action Recognition with RGB-D Sensors
Motion Tracking and Gesture Recognition
Autore/i: Cippitelli, Enea; Gambi, Ennio; Spinsante, Susanna
Editore: InTech Open
Luogo di pubblicazione: Rijeka
Classificazione: 2 Contributo in Volume
Abstract: Human action recognition, also known as HAR, is at the foundation of many different applications related to behavioral analysis, surveillance, and safety, thus it has been a very active research area in the last years. The release of inexpensive RGB-D sensors fostered researchers working in this field because depth data simplify the processing of visual data that could be otherwise difficult using classic RGB devices. Furthermore, the availability of depth data allows to implement solutions that are unobtrusive and privacy preserving with respect to classic video-based analysis. In this scenario, the aim of this chapter is to review the most salient techniques for HAR based on depth signal processing, providing some details on a specific method based on temporal pyramid of key poses, evaluated on the well-known MSR Action3D dataset.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250073 Collegamento a IRIS

2017 Multisensor data fusion for human activities classification and fall detection
2017 IEEE SENSORS
Autore/i: Li, Haobo; Shrestha, Aman; Fioranelli, Francesco; Le Kernec, Julien; Heidari, Hadi; Pepa, Matteo; Cippitelli, Enea; Gambi, Ennio; Spinsante, Susanna
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252590 Collegamento a IRIS

2017 Interoperability in IoT infrastructures for enhanced living environments
2016 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2016
Autore/i: Gambi, Ennio; Montanini, Laura; Raffaeli, Laura; Spinsante, Susanna; Lambrinos, Lambros
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The concept of Internet of Things is being applied in several areas and involves a dramatically increasing number of market sectors. There is a large variety of commercial products, and the competition between different vendors often causes incompatibility among the available solutions. Due to the lack of a reference standard, in the highly fragmented arena of Ambient Assisted Living systems and Smart Home environments, the support to interoperability is recognized as a key requirement for the deployment of successful products. This paper provides a state-of-the-art review of IoT adoption in the field of Ambient Assisted Living systems and Smart Home environments, by describing the most widespread solutions and their main key points, with a specific focus on the features designed to support interoperability. This is currently a matter of interest at a European level, as demonstrated, for example, by the inclusion of interoperability among the requirements that project proposals have to fulfill to be eligible for funding through the AAL Joint Platform calls published in the last years
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248305 Collegamento a IRIS

2017 Improved solution to monitor people with dementia and support care providers
Lecture Notes in Electrical Engineering
Autore/i: Raffaeli, Laura; Chiatti, CARLOS JUAN; Gambi, Ennio; Montanini, Laura; Olivetti, Paolo; Paciello, Luca; Rascioni, Giorgio; Spinsante, Susanna
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: Assistive Technologies offer the possibility to develop services aimed at improving the Quality of Life of patients and caregivers. Specifically, this work refers to the case of persons with dementia who can live in their homes but need to be assisted. This paper describes a monitoring kit that provides alarms to the caregiver in case of dangerous situations or unusual events detected by the sensors. It is composed by a set of non-intrusive sensors installed within the house, and can be configured in order to best fit with the needs of each patient. The proposed system could have the potentiality to reduce the stress that usually affects the caregivers, due to the continuous effort required and the worry about the patients’ safety. The improved system results from an existing solution that has been re-visited according to the feedbacks obtained from a pilot trial.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248051 Collegamento a IRIS

2017 An AAL-Oriented Measurement-based Evaluation of Different HTTP-based Data Transport Protocols
International Workshop on Protocols, Applications and Platforms for Enhanced Living Environments
Autore/i: Zinner, T.; Geissler, S.; Helmschrott, F.; Spinsante, Susanna; Braeken, A.
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: A key requirement for Active and Assisted Living (AAL) environments is the exchange of data between different communication endpoints to support wide range of services and applications. Used communication protocols need to support the bidirectional flow of information and have to be optimized with regard to security or latency constraints. To address these issues, RESTful approaches have recently gained much attention from the community. In this context, different application layer transport protocols can be used to realize the required data exchange. Besides HTTP/1.1, developed and standardized in the 1990s, new protocols like HTTP/2 and the QUIC transfer protocol my be suitable candidates. The impact of the different protocols on the overall performance for web and AAL services is still an open research question. This paper narrows this gap by conducting a measurement-based comparison of the three described protocols with regard to their performance in terms of web page loading times for Google web services.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248931 Collegamento a IRIS

2017 A prototype system for mm-wave channel characterization: Issues and results
Proceedings of 2017 IEEE Aerospace Conference
Autore/i: Spinsante, Susanna; Gambi, Ennio; DE SANTIS, Adelmo
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The deployment of new applications that can expand the mobile systems market is closely related to the availability of very high transmission capacity. Several researches are then developed to achieve this result, introducing as an example new modulation schemes or innovative channel coding technologies. With the aim to use a range of radio frequencies at present not crowded, and thus interference-free, able at the same time to make available a high bandwidth capacity, other researches are considering the possibility of transmitting at carrier frequencies of 60 GHz and beyond. The aim of this paper is to present a prototype for mm-Wave channel measurements, at 76 GHz, in order to derive a propagation model to be applied in different environmental conditions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248930 Collegamento a IRIS

2017 Android-Based Liveness Detection for Access Control in Smart Homes
Smart Objects and Technologies for Social Good Second International Conference, GOODTECHS 2016,Proceedings
Autore/i: Spinsante, Susanna; Montanini, Laura; Bartolucci, Veronica; Ricciuti, Manola; Gambi, Ennio
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: In the domain of smart homes, technologies for personal safety and security play a prominent role. This paper presents a low-complexity Android application designed for mobile and embedded devices, that exploits the on-board camera to easily capture two images of the subject, and processes them to discriminate a true 3D and live face from a 2D one. The liveness detection based on such a discrimination provides anti-spoofing capabilities to secure access control based on face recognition. The results obtained are satisfactory even in different ambient light conditions, and further improvements are being developed to deal with low precision image acquisition.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250249 Collegamento a IRIS

2017 Energy Efficient Communication in Ambient Assisted Living
Ambient Assisted Living and Enhanced Living Environments Principles, Technologies and Control
Autore/i: Chowdhury, Chandreyee; Aslam, Nauman; Spinsante, Susanna; Perla, Davide; DEL CAMPO, Antonio; Gambi, Ennio
Editore: Elsevier
Classificazione: 2 Contributo in Volume
Abstract: Recent advancements in Ambient Assisted Living (AAL) have produced innovative ways to address the needs of people with impairments and elderly improving their quality of life at the stage when it is most desirable. A typical AAL system consists of ubiquitous computing, sensing and communication blocks where wireless ad hoc, body area and sensor networks play a vital role to facilitate the transmission of sensed data from physiological and ambient sensors to the health-care professionals or monitoring facilities. While the end-to-end communication architecture in a typical AAL system remains heterogeneous, the key functional blocks of wireless body area and sensor network impose significant challenges concerning reliability, efficient use of spectrum and energy efficiency. This chapter focuses on an important challenge concerning energy efficient communication in a multi-tier AAL system. Following a thorough analysis of energy efficiency requirements for communication architectures and protocols in AAL, we provide recent research outputs highlighting the design and development of a multi-tier communication protocol. The proposed communication protocol focuses on inter-Body Area Network (BAN) communication.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250248 Collegamento a IRIS

2017 Supporting Caregivers in Nursing Homes for Alzheimer’s Disease Patients: A Technological Approach to Overnight Supervision
Information and Communication Technologies for Ageing Well and e-Health
Autore/i: Montanini, Laura; Raffaeli, Laura; DE SANTIS, Adelmo; DEL CAMPO, Antonio; Chiatti, CARLOS JUAN; Paciello, Luca; Gambi, Ennio; Spinsante, Susanna
Editore: Springer
Classificazione: 2 Contributo in Volume
Abstract: The reduction of public expenditure and investments in health care provisioning calls for new, sustainable models to transform the increasing aging population and dementia-related diseases incidence from global challenges into new opportunities. In this context, Information and Communication Technologies play a vital role, to both promote aging in place and home management of Patients with Dementia, and to provide new tools and solutions to facilitate the working conditions of the care staff in nursing homes, which remain an essential facility when cognitive-impaired patients cannot live at home anymore. Night staff in nursing homes are a vulnerable group, receiving less supervision and support than day staff, but with high levels of responsibility. Additionally, nighttime attendance of patients affected by dementia may be difficult, because of their incremented neuropsychiatric symptoms. This paper describes an integrated system for the night monitoring of patients with dementia in nursing homes, based on a product originally conceived for domestic use, but re-designed to provide support to nurses, by means of a set of sensors located in each patient’s room, and suitable software applications to detect dangerous events and raise automatic alerts delivered to the nurses through mobile devices. The results obtained from the first experimental installation of the monitoring system proved the effectiveness of the proposed solution to support nurses during the night supervision of patients, and suggested suitable modifications and additional features to increase the nurses’ compliance.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250246 Collegamento a IRIS

2017 Smartphones as Multipurpose Intelligent Objects for AAL: Two Case Studies
Smart Objects and Technologies for Social Good Second International Conference, GOODTECHS 2016,Proceedings
Autore/i: Spinsante, Susanna; Montanini, Laura; Gambi, Ennio; Lambrinos, Lambros; Pereira, Fábio; Pombo, Nuno; Garcia, Nuno
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: The increasing adoption of smartphones among older adults, especially in most developed countries, suggests they can be used not only for personal communications, but also in the framework of Active and Assisted Living solutions. This paper addresses two case studies in which a smartphone, when equipped with a proper software application, may operate as an inactivity monitor, and a drug management assistant, respectively. Activity monitoring is carried out by targeting the user’s interaction with the smartphone related to incoming, outgoing, and lost calls. In the latter case, an application processes images of drugs boxes captured by the smartphone camera, to automatically recognize the name of the drug, and inform the user about the corresponding prescription. Experimental results show this kind of approach is technically feasible and may provide satisfactory performance through a very easy interaction, thus supporting improved medication adherence by patients.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250250 Collegamento a IRIS

2017 The Human Factor in the Design of Successful Ambient Assisted Living Technologies
Ambient Assisted Living and Enhanced Living Environments - Principles, Technologies and Control
Autore/i: Spinsante, Susanna; Stara, Vera; Felici, Elisa; Montanini, Laura; Raffaeli, Laura; Rossi, Lorena; Gambi, Ennio
Editore: Elsevier
Classificazione: 2 Contributo in Volume
Abstract: The increasing incidence of ageing population in modern societies challenges the ability of families, states and communities to sustain new emerging needs. Assistive devices can help older people to maintain their ability in performing activities of daily living and, therefore, their independence. However, despite the huge public and private investments and efforts in research and development, the so-called silver market has not been able to grow at the expected pace: many barriers stand in the way leading from prototypes to products, especially when the target is an inhomogeneous group, as elderly people, and an explicit understanding of users, their needs, expectations and limitations, is not accounted for during the design process. This Chapter discusses the basic role of the human centric approach in the design of assistive technologies, and, by analyzing the outcomes of previous experiences, provides a set of guidelines that can help transforming a disruptive prototype into a successful product.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250247 Collegamento a IRIS

2017 Feature diversity for fall detection and human indoor activities classification using radar systems
Proceedings of IET International Conference on Radar Systems (Radar 2017)
Autore/i: Shrestha, A.; Le Kernec, J.; Fioranelli, F.; Cippitelli, E.; Gambi, E.; Spinsante, S.
Editore: IET
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269430 Collegamento a IRIS

2017 Radar and RGB-Depth Sensors for Fall Detection: A Review
IEEE SENSORS JOURNAL
Autore/i: Cippitelli, Enea; Fioranelli, Francesco; Gambi, Ennio; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth sensors for fall detection, and discusses the open research challenges and trends related to this research field. Systems to detect reliably fall events and promptly alert carers and first responders have gained significant interest in the past few years in order to address the societal issue of an increasing number of elderly people living alone, with the associated risk of them falling and the consequences in terms of health treatments, reduced well-being, and costs. The interest in radar and RGB-D sensors is related to their capability to enable contactless and non-intrusive monitoring, which may be an advantage for practical deployment and acceptance of indoor fall detection systems, with respect to other sensor technologies such as video-cameras, or wearables. Furthermore, the possibility of eventually combining and fusing information from heterogeneous types of sensors is expected to improve the overall performance of practical fall detection systems, hence researchers can benefit from multidisciplinary knowledge and awareness of the latest developments in different sensor fields.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/246517 Collegamento a IRIS

2017 Access Control in Smart Homes by Android-Based Liveness Detection
ICST TRANSACTIONS ON AMBIENT SYSTEMS
Autore/i: Spinsante, Susanna; Montanini, Laura; Bartolucci, Veronica; Ricciuti, Manola; Pigini, Danny; Gambi, Ennio
Classificazione: 1 Contributo su Rivista
Abstract: Technologies for personal safety and security play an increasing role in modern life, and are among the most valuable features expected to be supported by so-called smart homes. This paper presents a low-complexity Android application designed for both mobile and embedded devices, that exploits the available on-board camera to easily capture two images of a subject, and processes them to discriminate a true 3D and live face, from a fake or printed 2D one. The liveness detection based on such a discrimination provides antispoofing capabilities to secure access control based on face recognition. The limited computational complexity of the developed application makes it suitable for practical implementation in video-entry phones based on embedded Android platforms. The results obtained are satisfactory even in different ambient light conditions, and further improvements are being developed to deal with low precision image acquisition.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248929 Collegamento a IRIS

2017 Heart Rate Detection Using Microsoft Kinect: Validation and Comparison to Wearable Devices
SENSORS
Autore/i: Gambi, Ennio; Agostinelli, Angela; Belli, Alberto; Burattini, Laura; Cippitelli, Enea; Fioretti, Sandro; Pierleoni, Paola; Ricciuti, Manola; Sbrollini, Agnese; Spinsante, Susanna
Classificazione: 1 Contributo su Rivista
Abstract: Contactless detection is one of the new frontiers of technological innovation in the field of healthcare, enabling unobtrusive measurements of biomedical parameters. Compared to conventional methods for Heart Rate (HR) detection that employ expensive and/or uncomfortable devices, such as the Electrocardiograph (ECG) or pulse oximeter, contactless HR detection offers fast and continuous monitoring of heart activities and provides support for clinical analysis without the need for the user to wear a device. This paper presents a validation study for a contactless HR estimation method exploiting RGB (Red, Green, Blue) data from a Microsoft Kinect v2 device. This method, based on Eulerian Video Magnification (EVM), Photoplethysmography (PPG) and Videoplethysmography (VPG), can achieve performance comparable to classical approaches exploiting wearable systems, under specific test conditions. The output given by a Holter, which represents the gold-standard device used in the test for ECG extraction, is considered as the ground-truth, while a comparison with a commercial smartwatch is also included. The validation process is conducted with two modalities that differ for the availability of a priori knowledge about the subjects' normal HR. The two test modalities provide different results. In particular, the HR estimation differs from the ground-truth by 2% when the knowledge about the subject's lifestyle and his/her HR is considered and by 3.4% if no information about the person is taken into account.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250486 Collegamento a IRIS

2017 Analysis and Tools for Improved Management of Connectionless and Connection-Oriented BLE Devices Coexistence
SENSORS
Autore/i: DEL CAMPO, Antonio; Cintioni, Lorenzo; Spinsante, Susanna; Gambi, Ennio
Classificazione: 1 Contributo su Rivista
Abstract: With the introduction of low-power wireless technologies, like Bluetooth Low Energy (BLE), new applications are approaching the home automation, healthcare, fitness, automotive and consumer electronics markets. BLE devices are designed to maximize the battery life, i.e., to run for long time on a single coin-cell battery. In typical application scenarios of home automation and Ambient Assisted Living (AAL), the sensors that monitor relatively unpredictable and rare events should coexist with other sensors that continuously communicate health or environmental parameter measurements. The former usually work in connectionless mode, acting as advertisers, while the latter need a persistent connection, acting as slave nodes. The coexistence of connectionless and connection-oriented networks, that share the same central node, can be required to reduce the number of handling devices, thus keeping the network complexity low and limiting the packet's traffic congestion. In this paper, the medium access management, operated by the central node, has been modeled, focusing on the scheduling procedure in both connectionless and connection-oriented communication. The models have been merged to provide a tool supporting the configuration design of BLE devices, during the network design phase that precedes the real implementation. The results highlight the suitability of the proposed tool: the ability to set the device parameters to allow us to keep a practical discovery latency for event-driven sensors and avoid undesired overlaps between scheduled scanning and connection phases due to bad management performed by the central node.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/246266 Collegamento a IRIS

2017 A LoRa enabled building automation architecture based on MQTT
AEIT International Annual Conference, 2017
Autore/i: Spinsante, Susanna; Ciattaglia, Gianluca; Del Campo, Antonio; Perla, Davide; Pigini, Danny; Cancellieri, Giovanni; Gambi, Ennio
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252589 Collegamento a IRIS

2016 Integrated Smart TV-Based Personal e-Health System
INTERNATIONAL JOURNAL OF E-HEALTH AND MEDICAL COMMUNICATIONS
Autore/i: Raffaeli, Laura; Susanna, Spinsante; Ennio, Gambi
Classificazione: 1 Contributo su Rivista
Abstract: This paper discusses the design and experimental implementation of an integrated system for the delivery of health related services, based on different technologies and devices. The idea is to create a unique point of access for the user, towards both a cloud-based remote service for the consultation of medical reports, and a personal local service that allows to collect and display data from biomedical sensors, to manage user's reminders for medicines, and to monitor the patient's dietary habits. The proposed system employs suitable technologies to simplify the user interaction, such as Near Field Communications enabled devices, and a smart TV equipment. By this way, it is possible to effectively deliver telehealth services also to users who may be less familiar with technological equipments, such as older adults, or people living in rural communities. The experimental implementation proves the feasibility of the proposed service, and the possibility to gain users' adherence and compliance, through proper design criteria.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/234270 Collegamento a IRIS

2016 Data Management in Ambient Assisted Living Platforms Approaching IoT: A Case Study
2015 IEEE Globecom Workshops (GC Wkshps)
Autore/i: Spinsante, S.; Gambi, E.; Montanini, L.; Raffaeli, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The adoption of the Internet of Things paradigm in Ambient Assisted Living platforms requires the investigation and analysis of issues related to data collection and processing. In fact, the peculiarities of Ambient Assisted Living services and applications pose specific requirements on the way data originated from sensors should be processed (locally or remotely), delivered (as raw data, or in aggregated fashion), and, of course, how they should be shared or protected. This paper analyses the issues related to data management starting from a review of the state of the art, in order to draw general trends or widespread approaches, that are then discussed and evaluated with respect to a practical implementation presented as a case study.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/234168 Collegamento a IRIS

2016 Secure end-to-end communication for constrained devices in IoT-enabled Ambient Assisted Living systems
2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)
Autore/i: Porambage, P.; Braeken, A.; Gurtov, A.; Ylianttila, M.; Spinsante, S.
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/234169 Collegamento a IRIS

2016 Evaluation of a skeleton-based method for human activity recognition on a large-scale RGB-D dataset
IET Conference Publications
Autore/i: Cippitelli, Enea; Gambi, Ennio; Spinsante, Susanna; Flórez-Revuelta, Francisco
Editore: Institution of Engineering and Technology
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248302 Collegamento a IRIS

2016 MQTT in AAL systems for home monitoring of people with dementia
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Autore/i: DEL CAMPO, Antonio; Gambi, Ennio; Montanini, Laura; Perla, Davide; Raffaeli, Laura; Spinsante, Susanna
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248296 Collegamento a IRIS

2016 Improving the quality of user generated data sets for activity recognition
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Autore/i: Nugent, Chris; Synnott, Jonathan; Gabrielli, Celeste; Zhang, Shuai; Espinilla, Macarena; Calzada, Alberto; Lundstrom, Jens; Cleland, Ian; Synnes, Kare; Hallberg, Josef; Spinsante, Susanna; Barrios, Miguel Angel Ortiz
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248304 Collegamento a IRIS

2016 User interfaces in smart assistive environments: Requirements, devices, applications
Handbook of Research on Human-Computer Interfaces, Developments, and Applications
Autore/i: Raffaeli, Laura; Montanini, Laura; Gambi, Ennio; Spinsante, Susanna
Editore: IGI Global
Classificazione: 2 Contributo in Volume
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248299 Collegamento a IRIS

2016 An integrated approach to fall detection and fall risk estimation based on RGB-depth and inertial sensors
ACM International Conference Proceeding Series
Autore/i: Cippitelli, Enea; Gasparrini, Samuele; Gambi, Ennio; Spinsante, Susanna
Editore: Association for Computing Machinery
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248297 Collegamento a IRIS

2016 Proposal and experimental evaluation of fall detection solution based on wearable and depth data fusion
Advances in Intelligent Systems and Computing
Autore/i: Gasparrini, Samuele; Cippitelli, Enea; Gambi, Ennio; Spinsante, Susanna; Wåhslén, J.; Orhan, I.; Lindh, T.
Editore: Springer-Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fall injury issues represent a serious problem for elderly in our society. These people want to live in their home as long as possible and technology can improve their security and independence. In this work we study the joint use of a camera based system and wearable devices, in the so called data fusion approach, to design a fall detection solution. The synchronization issues between the heterogeneous data provided by the devices are properly treated, and three different fall detection algorithms are implemented. Experimental results are also provided, to compare the proposed solutions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/236340 Collegamento a IRIS

2016 Unobtrusive intake actions monitoring through RGB and depth information fusion
Proceedings - 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing, ICCP 2016
Autore/i: Cippitelli, Enea; Gasparrini, Samuele; Gambi, Ennio; Spinsante, Susanna
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248298 Collegamento a IRIS

2016 Feasibility of e-health services through the smart TV: A prototype demonstrator
INTERNATIONAL JOURNAL OF MEDICAL ENGINEERING AND INFORMATICS
Autore/i: Raffaeli, Laura; Spinsante, Susanna; Gambi, Ennio
Classificazione: 1 Contributo su Rivista
Abstract: Public institutions worldwide are moving a number of services targeted to citizens from traditional data infrastructures to cloud based technologies, with the aim of improving the quality offered, and reducing costs. This phenomenon is particularly relevant in the field of health-related public services. Among the technological devices and media enabling users' access to such services, the emerging smart TV platform represents a promising and valid means of interaction. In many countries, where population ageing is becoming the leading welfare concern, information and communication technologies are expected to play a basic role in alleviating the pressure on public healthcare services. In this scenario, the paper discusses the feasibility of an e-health service delivered through the smart TV, by the design and implementation of a prototype application that enables the remote consultation of personal medical reports. Users can access their personal health records, and visualise the outcomes of medical examinations performed at a specific laboratory by interacting with the smart TV through its remote controller.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240506 Collegamento a IRIS

2016 TST Intake Monitoring dataset V1
TST Intake Monitoring dataset v1
Autore/i: Cippitelli, E.; Gambi, E.; Gasparrini, S.; Spinsante, S.
Classificazione: 5 Altro
Abstract: The dataset contains depth frames collected using Microsoft Kinect v1 during the execution of food and drink intake movements.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240014 Collegamento a IRIS

2016 Human action recognition based on temporal pyramid of key poses using RGB-D sensors
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Autore/i: Cippitelli, Enea; Gambi, Ennio; Spinsante, Susanna; Florez-Revuelta, Francisco
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240504 Collegamento a IRIS

2016 Overnight supervision of Alzheimer's disease patients in nursing homes: System development and field trial
ICT4AWE 2016 - 2nd International Conference on Information and Communication Technologies for Ageing Well and e-Health, Proceedings
Autore/i: Montanini, Laura; Raffaeli, Laura; De Santis, Adelmo; Del Campo, Antonio; Chiatti, Carlos; Rascioni, Giorgio; Gambi, Ennio; Spinsante, Susanna
Editore: SciTePress
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240926 Collegamento a IRIS

2016 An OpenCV based android application for drowsiness detection on mobile devices
Lecture Notes in Electrical Engineering Code 179299
Autore/i: Montanini, Laura; Gambi, Ennio; Spinsante, Susanna
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/236644 Collegamento a IRIS

2016 BLE analysis and experimental evaluation in a walking monitoring device for elderly
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Autore/i: DEL CAMPO, Antonio; Montanini, Laura; Perla, Davide; Gambi, Ennio; Spinsante, Susanna
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/248295 Collegamento a IRIS


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