The need to increase support for healthy ageing and longevity research in the EU by establishing a Coordination and Support Programme on Healthy Ageing and Longevity Ilia Stambler, Alexander Tietz-Latza, Björn Schumacher, Hartmut Geiger, Helen Morrison, Oliver Tüscher, Georg Fuellen, Roland Meisel, Andreas Simm, Andreas Pfeiffer, Axel Steinhage, Aurel Popa-Wagner, Wolfgang Wagner, Oliver Cornely, Mario Krause, Georgios Mitrou, Marios Kyriazis, Morten Scheibye-Knudsen, Suresh Rattan, Richard Siow, David Weinkove, Shuvarthi Bhattacharjee, Didier Coeurnelle, Niccolò Invidia, Nicola Marino, Maddalena Illario, Calogero Caruso, Ennio Tasciotti, Federico Schena, Francesca Cesaroni, Salvatore De Rosa, Francesco Neri, Dmitry Bulavin, John Rowell, Bruno Vellas, Edouard Debonneuil, Lilia Lens-Pechakova, José Luis Cordeiro, Eduardo Díaz-Rubio, María Cordón Muro, Mayca Marín, Cayetano Santana Gil, Sergio Guillen, Dolores Corella, Pedro Barata, Amelia Pilar Rauter, Mónica Sousa, Linus Petersson, Brun Ulfhake, Valdis Pīrāgs, Svjatoslavs Kistkins, Emīls Sjundjukovs, Dmitrijs Bliznuks, Leonas Valius, Silvija Valdonė Alšauskė, Maria Teresa Arredondo, Marek Postula, Igors Berkovics, Karol Kaminski, Antonella Santuccione Chadha, Evelyne Bischof, Alessandro Puiatti, Raluca Prodan, Ionel Blănculescu, Lacramioara Frasineanu, Anca Andreea Sandu, Milena Georgieva, Angel Marchev, Angel Marchev, Alexander Tchernev, Martin Lipovšek, Dóra Horváth, Harald Sourij, Hana Vankova, Marjolein Visser, Kinga Matuła, Oleh Lushchak, Zoia Dikhtiarenko, Abraham Kebede, Rada Sandic-Spaho, Michelle Adams, Efstathios S. Gonos Mechanisms of Ageing and Development, 2026 Europe faces rapidly accelerating population ageing, driving multimorbidity and unsustainable healthcare costs. This paper calls for the establishment of an EU Coordination and Support Programme on Healthy Ageing and Longevity to integrate research, innovation, regulation, and capacity‑building across Member States.
Toward unbiased emotion recognition: overcoming user bias with siamese convolutional networks Nicolò La Porta, Gilles Oldano, Alessandro Puiatti, Tiziano Leidi, Michela Papandrea Signal Image and Video Processing, 2025 Purpose: Emotion Recognition (ER) systems are designed for an accurate inference of human emotions. Emotions are elicited by stimuli provided by the environment, such as social interactions or exposure to salient events, and are expressed by individuals in a strictly subjective manner. ER systems are usually based on machine learning approaches applied to physiological signals, which provide an authentic representation of emotions as they are not easily controlled or masked. However, ER remains a challenging task, due to a well-established user bias related to individual response specificity (IRS). When multiple subjects are considered together in a dataset, IRS makes the ER task more difficult at the dataset level than at the subject level. Methods: In this work, we accomplish a multi-class ER task based on physiological signals while addressing the user bias problem. We propose a mitigation strategy based on Siamese Convolutional Networks (SCN). We perform a qualitative and quantitative analysis of user bias, comparing the feature space of the proposed SCN with a baseline hand-crafted feature space. Results: Our SCN reached state-of-the-art performance in the considered multi-class ER task and showed great capability of disentangling user bias, by reducing the gap between subject-level and dataset-level metrics. Conclusion: Our main contribution is the proposal of a user bias mitigation strategy for ER tasks, which takes advantage of the SCN capability of producing subject-independent latent representations.
Sleep Apnea Events Recognition Based on Polysomnographic Recordings: A Large-Scale Multi-Channel Machine Learning approach Nicolò La Porta, Stefano Scafa, Michela Papandrea, Filippo Molinari, Alessandro Puiatti IEEE Open Journal of Engineering in Medicine and Biology, 2025 — Goal: The gold standard for detecting the presence of apneic events is a time and effort-consuming manual evaluation of type I polysomnographic recordings by experts, often not error-free. Such acquisition protocol requires dedicated facilities resulting in high costs and long waiting lists. The usage of artificial intelligence models assists the clinician’s evaluation overcoming the aforementioned limitations and increasing healthcare quality. Methods: The present work proposes a machine learning-based approach for automatically recognizing apneic events in subjects affected by sleep apnea-hypopnea syndrome. It embraces a vast and diverse pool of subjects, the Wisconsin Sleep Cohort (WSC) database. Results: An overall accuracy of 87.2 ± 1.8% is reached for the event detection task, significantly higher than other works in literature performed over the same dataset. The distinction between different types of apnea was also studied, obtaining an overall accuracy of 62.9 ± 4.1%. Conclusions: The proposed approach for sleep apnea events recognition, validated over a wide pool of subjects, enlarges the landscape of possibilities for sleep apnea events recognition, identifying a subset of signal that improves SoA performances and guarantees simple interpretation.
G.A.I.T: gait analysis interactive tool a pipeline for automatic detection of gait events across different motor impairments Matteo Nocilli, Stefano Scafa, Nicolò La Porta, Marco Ghislieri, Valentina Agostini, Eduardo M. Moraud, Alessandro Puiatti Signal Image and Video Processing, 2024 We introduce an open-access tool capable of automatically extracting the timing of gait events during unconstrained locomotion across different neuromotor impairments. The gait analysis interactive tool is conceived as an assistant for gait assessment studies, both in healthy participants or in people with motor impairments affecting gait symmetry, regularity, or balance, as usually encountered in patients with neurological disorders. Our open-access pipeline makes it possible to automatically identify the time of key gait events (heel strike, toe off) from a single gyroscope axis (lateral mid-axis), simplifying experimental protocols, and can easily be used in everyday life conditions. The code is user-friendly and interactive. At each stage of analysis, it allows for possible adjustments and manual corrections of undetected or mismatched events. To implement, test, and validate our algorithm, we used three different databases of gait recordings that span from healthy subjects to patients affected by Parkinson’s disease. The pipeline consists of three main sections that allow us to segment, identify, and eventually correct the events within the gait cycle. The algorithm achieved an average accuracy of 99.23% over healthy participants, either with average weight or overweight, and a performance of 94.84% over patients with Parkinson’s disease. Even if gait analysis is a widely studied problem, so far, no open-source algorithm is available. The present work provides an easy tool capable of working with a minimum set of sensors and without any expensive platform or camera-based system. Employing three databases widely different for the environment, and for the subjects’ age and motor impairments highlights the versatility of our approach.
Game-based Training of Cognitive Functions: an Exploratory Study Involving Seniors in Switzerland Sara Levati, Massimo Bortolamei, Lucia Morellini, Jessica Demarchi, Matteo Metaldi, Alessandro Puiatti, Masiar Babazadeh Proceedings of the European Conference on Games Based Learning, 2024 The aging population is resulting in a worldwide rising prevalence of individuals experiencing cognitive decline, whether it be normal age-related changes or pathological conditions. Game-based training in the form of serious games represents an alternative way to enhance cognitive functions among older people. We developed a set of games to train multiple cognitive functions of seniors, considering that their level of digital literacy can vary greatly. A participatory approach has been applied to the development process, involving a multidisciplinary research team and older people. Interviews, usability tests, and a workshop were run with ten seniors (70+) in Southern Switzerland to explore accessibility, usability, and preferences. This paper presents the development process and the games created. Six different games were designed to stimulate multiple cognitive functionalities (e.g., cognitive flexibility, attentiveness, and memory). The serious games run on a tablet. Following Laamarti’s classification, we developed the games to be applied in well-being and health areas, requiring mainly mental activities through visual modalities, played through a touchscreen in a 2D digital environment. Participants appreciated the experience and the challenges provided by the games, understanding the broader aim (cognitive functions training) and the rules, and could complete the required tasks. Feedback was provided on graphical elements (icons and colours), as well as with suggestions for improvements. The tablet appeared to be functional and relatively easy to use, even for first timers. The promising results of this participatory study pave the way for the follow-up phase of the project, which will gather data on the usage of the application and its effectiveness with a greater number of subjects.
Unobtrusive Human Fall Detection System Using mmWave Radar and Data Driven Methods Ariyamehr Rezaei, Alessandro Mascheroni, Michael C. Stevens, Reza Argha, Michela Papandrea, Alessandro Puiatti, Nigel H. Lovell IEEE Sensors Journal, 2023 As the population ages, health issues like injurious falls demand more attention. One solution is to use wearable devices to detect falls. Nevertheless, most of these devices raise obtrusiveness, and older people generally resist or might forget to wear them. The millimeter-wave (mmWave) radar technology was used in this study to unobtrusively detect human falls. Data were collected from healthy young volunteers with the radar mounted on the side wall (trial 1) or overhead (trial 2) of an experimental room. A set of features were manually extracted from the data point clouds; then, multilayer perceptron (MLP), random forest (RF), <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -nearest neighbor (KNN), and support vector machine (SVM) classifiers were applied on the features. Additionally, we devised a convolutional neural network (CNN)-based deep learning model for the underlying fall detection problem that receives a 3-D representation of the point cloud data, known as occupancy grid, as the input. The optimal installation position of the radar sensor was unknown. Therefore, the sensor was mounted on side wall and on the ceiling of the room to allow the performance comparison between these sensor placements. RF classifier achieved the best results in trial 2 (an accuracy of 92.2%, a recall of 0.881, a precision of 0.805, and an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${F}1$ </tex-math></inline-formula> -score of 0.841), and the proposed CNN model achieved slightly better results comparing to the RF method in trial 2 (an accuracy of 92.3%, a recall of 0.891, a precision of 0.801, and an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${F}1$ </tex-math></inline-formula> -score of 0.844). These results suggest that the development of an unobtrusive monitoring system for fall detection using mmWave radar is feasible.
Actigraphy Enables Home Screening of Rapid Eye Movement Behavior Disorder in Parkinson's Disease Flavio Raschellà, Stefano Scafa, Alessandro Puiatti, Eduardo Martin Moraud, Pietro‐Luca Ratti Annals of Neurology, 2023 OBJECTIVES REM sleep behavior disorder (RBD) is a potentially harmful, often overlooked sleep disorder affecting up to 70% of Parkinson's disease patients. Current diagnosis relies on nocturnal video-polysomnography, which is an expensive and cumbersome exam requiring specific clinical expertise. Here, we explored the use of wrist actigraphy to enable automatic RBD diagnoses in home settings. METHODS Twenty-six Parkinson's patients underwent two-week home wrist actigraphy, followed by two in-lab evaluations. Patients were classified as RBD vs. non-RBD based on dream enactment history and video-polysomnography. We comprehensively characterized patients' movement patterns during sleep using actigraphic signals. We then trained machine learning classification algorithms to discriminate patients with or without RBD using the most relevant features. Classification performance was quantified with respect to clinical diagnosis, separately for in-lab and at-home recordings. Performance was further validated in a control group of non-PD patients with other sleep conditions. RESULTS To characterize RBD, actigraphic features extracted from both (i) individual movement episodes and (ii) global nocturnal activity were critical. RBD patients were more active overall, and exhibited movements that were shorter, of higher magnitude, and more scattered in time. Using these features, our classification algorithms reached an accuracy of 92.9±8.16% during in-clinic tests. When validated on home recordings in Parkinson's patients, accuracy reached 100% over a two-week window, and was 94.4% in non-PD control patients. Features showed robustness across tests and conditions. INTERPRETATIONS These results open new perspectives for faster, cheaper, and more regular screening of sleep disorders, both for routine clinical practice and clinical trials. This article is protected by copyright. All rights reserved.
Entreprenursery: Taking Care of Ideas Mauro Citraro, Cristina Carcano-Monti, Simone Pellegrini, Alessandro Puiatti, Lorenzo Sommaruga IEEE Global Engineering Education Conference Educon, 2023 The birth of a student entrepreneurial idea needs a delivery room and a research methodology. It should be nourished to grow like a nursery takes care of its offspring for them to become healthy adults. The initial birth of a startup idea needs encouragement, assistance and protection. Entreprenursery's main goal is to bring to life ideas and to help them develop once discovered. In this respect, Entreprenursery, working as an accelerator of ideas, is built on stakeholders who take care of the student's inclination for entrepreneurship. Entreprenursery is characterized by an informal teaching approach that breaks down barriers, fosters involvement and creates an enjoyable working atmosphere within students, mentors, corporates and entrepreneurial members of the society. All of them are part of a quadruple helix model in which the main actors are students leading their startup ideas to innovation. A digital platform – pingel@p – manages the collection and helps all stakeholders to work together to reach a common goal: allowing startup ideas to grow in a safe but encouraging environment by taking care of the intellectual property (IP) as well. Providing IP protection gives students a nurtured feeling and a sense of ownership. In Entreprenursery, students are also confronted with companies expressing their business needs and challenges, allowing entrepreneurial students to take them up.
Principles of gait encoding in the subthalamic nucleus of people with Parkinson's disease Yohann Thenaisie, Kyuhwa Lee, Charlotte Moerman, Stefano Scafa, Andrea Gálvez, Elvira Pirondini, Morgane Burri, Jimmy Ravier, Alessandro Puiatti, Ettore Accolla, Benoit Wicki, André Zacharia, Mayte Castro Jiménez, Julien F. Bally, Grégoire Courtine, Jocelyne Bloch, Eduardo Martin Moraud Science Translational Medicine, 2022
FROM CREATIVITY TO VALUE CREATION Mauro Citraro, Cristina Carcano, Emanuele Carpanzano, Alessandro Puiatti, Lorenzo Sommaruga, et al. Sefi 2022 50th Annual Conference of the European Society for Engineering Education Proceedings, 2022
Child Head Gesture Classification through Transformers Nushara Wedasingha, Pradeepa Samarasinghe, Dharshika Singarathnam, Michela Papandrea, Alessandro Puiatti, Lasantha Seneviratne IEEE Region 10 Annual International Conference Proceedings TENCON, 2022
Skeleton Based Periodicity Analysis of Repetitive Actions Nushara Wedasingha, Pradeepa Samarasinghe, Lasantha Seneviratne, Alessandro Puiatti, Michela Papandrea, Dulangi Dhanayaka 2022 IEEE 7th International Conference for Convergence in Technology I2ct 2022, 2022
Sensor Data Synchronization in a IoT Environment for Infants Motricity Measurement Simone Sguazza, Alessandro Puiatti, Sandra Bernaschina, Francesca Faraci, Gianpaolo Ramelli, Vincenzo D’Apuzzo, Emmanuelle Rossini, Michela Papandrea Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2020
Automated sleep scoring: A review of the latest approaches Luigi Fiorillo, Alessandro Puiatti, Michela Papandrea, Pietro-Luca Ratti, Paolo Favaro, Corinne Roth, Panagiotis Bargiotas, Claudio L. Bassetti, Francesca D. Faraci Sleep Medicine Reviews, 2019
A New Prospective, Home-Based Monitoring of Motor Symptoms in Parkinson's Disease Pietro-Luca Ratti, Francesca Faraci, Sandra Hackethal, Alessandro Mascheroni, Clara Ferlito, Serena Caverzasio, Ninfa Amato, Eun Kyoung Choe, Yuhan Luo, Paulo-Edson Nunes-Ferreira, Salvatore Galati, Alessandro Puiatti, Alain Kaelin-Lang Journal of Parkinson S Disease, 2019
AutoPlay: A smart toys-kit for an objective analysis of children ludic behavior and development Francesca D. Faraci, Michela Papandrea, Alessandro Puiatti, Stefania Agustoni, Sara Giulivi, Vincenzo DrApuzzo, Silvia Giordano, Flavio Righi, Olmo Barberis, Evelyne Thommen, Emmanuelle Rossini Memea 2018 2018 IEEE International Symposium on Medical Measurements and Applications Proceedings, 2018
Personal health systems for bipolar disorder Anecdotes, challenges and lessons learnt from MONARCA project Oscar Mayora, Bert Arnrich, Jakob Bardram, Carsten Dräger, Andrea Finke, Mads Frost, Silvia Giordano, Franz Gravenhorst, Agnes Grunerbl, Christian Haring, Reinhold Haux, Paul Lukowicz, Amir Muaremi, Steven Mudda, Stefan Ohler, Alessandro Puiatti, Nina Reichwaldt, Corinna Scharnweber, Gerhard Troester, Lars Vedel Kessing, Gabriel Wurzer Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops Pervasivehealth 2013, 2013
A wireless sensor networks platform for modelling space perception during saccadic eye-movements Proceedings of the 12th Imeko Tc1 Education and Training in Measurement and Instrumentation and Tc7 Measurement Science Joint Symposium on Man Science and Measurement 2008, 2008
Enhanced DHCP client Silvia Giordano, Davide Lenzarini, Alessandro Puiatti, Salvatore Vanini Proceedings of the Annual International Conference on Mobile Computing and Networking MOBICOM, 2007
Design of an enhanced MAC architecture for multi-hop wireless networks Multi Hop Ad Hoc Networks from Theory to Reality, 2007
Enhanced DHCP client Mobicom 07 Co Located Workshops Proceedings of the 2nd ACM Workshop on Challenged Networks Chants 07, 2007
Deployable application layer solution for seamless mobility across heterogeneous networks Ad Hoc and Sensor Wireless Networks, 2007
Demonstrating seamless handover of multi-hop networks Silvia Giordano, Davide Lenzarini, Alessandro Puiatti, Mirko Kulig, Hoang Nguyen, Salvatore Vanini Realman 2006 Proceedings of Second International Workshop on Multi Hop Ad Hoc Networks from Theory to Reality, 2006
A cross-layering and autonomic approach to optimized seamless handover Wons 2006 3rd International Conference on Wireless on Demand Network Systems and Services, 2006
An enhanced MAC architecture for multi-hop wireless networks R. Bernasconi, I. Defilippis, S. Giordano, A. Puiatti Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2003
RECENT SCHOLAR PUBLICATIONS
The need to increase support for healthy ageing and longevity research in the EU by establishing a Coordination and Support Programme on Healthy Ageing and Longevity I Stambler, A Tietz-Latza, B Schumacher, H Geiger, H Morrison, ... Mechanisms of ageing and development, 112187 , 2026 2026
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Subthalamic nucleus encoding steers adaptive therapies for gait in Parkinson’s disease S Scafa, V de Seta, R Wang, PS López, C Varescon, I Sakr, N Bérard, ... medRxiv, 2025.08. 20.25333478 , 2025 2025 Citations: 1
Autoencoder based data clustering for identifying anomalous repetitive hand movements, and behavioral transition patterns in children N Wedasingha, P Samarasinghe, L Senevirathna, M Papandrea, A Puiatti Physical and Engineering Sciences in Medicine 48 (1), 221-238 , 2025 2025
GAIT: gait analysis interactive tool a pipeline for automatic detection of gait events across different motor impairments M Nocilli, S Scafa, N La Porta, M Ghislieri, V Agostini, EM Moraud, ... Signal, Image and Video Processing 18 (12), 8499-8506 , 2024 2024 Citations: 6
Sleep apnea events recognition based on polysomnographic recordings: a large-scale multi-channel machine learning approach N La Porta, S Scafa, M Papandrea, F Molinari, A Puiatti IEEE open journal of engineering in medicine and biology 6, 202-211 , 2024 2024 Citations: 2
Game-based training of cognitive functions: an exploratory study involving seniors in Switzerland S Levati, M Bortolamei, L Morellini, J Demarchi, M Metaldi, A Puiatti, ... European Conference on Games Based Learning, 541-550 , 2024 2024 Citations: 2
Auto-encoder Based Data Clustering for Typical and Atypical Repetitive Child Hand Movement Pattern Identification N Wedasingha, P Samarasinhe, L Seneviratne, M Papandrea, A Puiatti SLIIT, Faculty of Engineering , 2024 2024
Real-Time Decoding of Leg Motor Function and Dysfunction from the Subthalamic Nucleus in People with Parkinson’s Disease K Lee, Y Thenaisie, C Moerman, S Scafa, A Gálvez, E Pirondini, M Burri, ... Brain-Computer Interface Research: A State-of-the-Art Summary 11, 83-92 , 2024 2024 Citations: 1
Automated anomalous child repetitive head movement identification through transformer networks N Wedasingha, P Samarasinghe, L Senevirathna, M Papandrea, A Puiatti, ... Physical and Engineering Sciences in Medicine 46 (4), 1427-1445 , 2023 2023 Citations: 3
Entreprenursery: Taking care of ideas M Citraro, C Carcano-Monti, S Pellegrini, A Puiatti, L Sommaruga 2023 IEEE Global Engineering Education Conference (EDUCON), 1-6 , 2023 2023 Citations: 3
Unobtrusive human fall detection system using mmwave radar and data driven methods A Rezaei, A Mascheroni, MC Stevens, R Argha, M Papandrea, A Puiatti, ... IEEE sensors journal 23 (7), 7968-7976 , 2023 2023 Citations: 75
Actigraphy enables home screening of rapid eye movement behavior disorder in Parkinson's disease F Raschellà, S Scafa, A Puiatti, E Martin Moraud, PL Ratti Annals of Neurology 93 (2), 317-329 , 2023 2023 Citations: 40
Child head gesture classification through transformers N Wedasingha, P Samarasinghe, D Singarathnam, M Papandrea, ... TENCON 2022-2022 IEEE Region 10 Conference (TENCON), 1-6 , 2022 2022 Citations: 1
Actigraphy enables home screening of REM behavior disorder in Parkinson's disease: Preliminary data F Raschella, S Scafa, A Puiatti, E Martin-Moraud, PL Ratti Journal Of Sleep Research 31 , 2022 2022
Principle of gait encoding in the subthalamic nucleus of people with Parkinson's disease MEM Thenaisie Y, Lee K, Moerman C, Scafa S, Gálvez A, Pirondini E, Burri M ... Science Tran. Med., DOI:10.1126/scitranslmed.abo1800 , 2022 2022
Principles of gait encoding in the subthalamic nucleus of people with Parkinson’s disease Y Thenaisie, K Lee, C Moerman, S Scafa, A Gálvez, E Pirondini, M Burri, ... Science translational medicine 14 (661), eabo1800 , 2022 2022 Citations: 75
An unobtrusive human activity recognition system using low resolution thermal sensors, machine and deep learning A Rezaei, MC Stevens, A Argha, A Mascheroni, A Puiatti, NH Lovell IEEE Transactions on Biomedical Engineering 70 (1), 115-124 , 2022 2022 Citations: 50
Skeleton based periodicity analysis of repetitive actions N Wedasingha, P Samarasinghe, L Seneviratne, A Puiatti, M Papandrea, ... 2022 IEEE 7th International conference for Convergence in Technology (I2CT), 1-6 , 2022 2022 Citations: 2
RBDAct: Home screening of REM sleep behaviour disorder based on wrist actigraphy in Parkinson’s patients F Raschellà, S Scafa, A Puiatti, E Martin Moraud, PL Ratti medRxiv, 2022.01. 23.22269713 , 2022 2022 Citations: 6
MOST CITED SCHOLAR PUBLICATIONS
Automated sleep scoring: A review of the latest approaches L Fiorillo, A Puiatti, M Papandrea, PL Ratti, P Favaro, C Roth, P Bargiotas, ... Sleep medicine reviews 48, 101204 , 2019 2019 Citations: 354
Probabilistic routing protocol for intermittently connected mobile ad hoc network (propicman) HA Nguyen, S Giordano, A Puiatti 2007 IEEE international symposium on a world of wireless, mobile and … , 2007 2007 Citations: 134
Smartphone-centred wearable sensors network for monitoring patients with bipolar disorder A Puiatti, S Mudda, S Giordano, O Mayora 2011 Annual International Conference of the IEEE Engineering in Medicine and … , 2011 2011 Citations: 107
Unobtrusive human fall detection system using mmwave radar and data driven methods A Rezaei, A Mascheroni, MC Stevens, R Argha, M Papandrea, A Puiatti, ... IEEE sensors journal 23 (7), 7968-7976 , 2023 2023 Citations: 75
Principles of gait encoding in the subthalamic nucleus of people with Parkinson’s disease Y Thenaisie, K Lee, C Moerman, S Scafa, A Gálvez, E Pirondini, M Burri, ... Science translational medicine 14 (661), eabo1800 , 2022 2022 Citations: 75
An unobtrusive human activity recognition system using low resolution thermal sensors, machine and deep learning A Rezaei, MC Stevens, A Argha, A Mascheroni, A Puiatti, NH Lovell IEEE Transactions on Biomedical Engineering 70 (1), 115-124 , 2022 2022 Citations: 50
Actigraphy enables home screening of rapid eye movement behavior disorder in Parkinson's disease F Raschellà, S Scafa, A Puiatti, E Martin Moraud, PL Ratti Annals of Neurology 93 (2), 317-329 , 2023 2023 Citations: 40
Personal health systems for bipolar disorder anecdotes, challenges and lessons learnt from monarca project O Mayora, B Arnrich, J Bardram, C Dräger, A Finke, M Frost, S Giordano, ... 2013 7th International Conference on Pervasive Computing Technologies for … , 2013 2013 Citations: 40
Wireless sensor networks for planetary exploration: Experimental assessment of communication and deployment D Sanz, A Barrientos, M Garzón, C Rossi, M Mura, D Puccinelli, A Puiatti, ... Advances in Space Research 52 (6), 1029-1046 , 2013 2013 Citations: 22
Development of a platform to combine sensor networks and home robots to improve fall detection in the home environment L Della Toffola, S Patel, B Chen, YM Ozsecen, A Puiatti, P Bonato 2011 Annual International Conference of the IEEE Engineering in Medicine and … , 2011 2011 Citations: 22
A cross-layering and autonomic approach to optimized seamless handover GA Di Caro, S Giordano, M Kulig, D Lenzarini, A Puiatti, F Schwitter WONS 2006: Third Annual Conference on Wireless On-demand Network Systems and … , 2006 2006 Citations: 22
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Wiswitch: Seamless handover between multi-provider networks S Giordano, D Lenzarini, A Puiatti, S Vanini Second Annual Conference on Wireless On-demand Network Systems and Services … , 2005 2005 Citations: 20
Activity detection in uncontrolled free-living conditions using a single accelerometer SI Lee, MY Ozsecen, L Della Toffola, JF Daneault, A Puiatti, S Patel, ... 2015 IEEE 12th International Conference on Wearable and Implantable Body … , 2015 2015 Citations: 17
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Mobile and Ubiquitous Systems: Computing, Networking, and Services APT Gu 2013 Citations: 14
UWB tracking for home care systems with off-the-shelf components E Bonizzoni, A Puiatti, S Sapienza, PM Ros, D Demarchi, P Bonato 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5 , 2018 2018 Citations: 13
AutoPlay: a smart toys-kit for an objective analysis of children ludic behavior and development FD Faraci, M Papandrea, A Puiatti, S Agustoni, S Giulivi, V D’Apuzzo, ... 2018 IEEE International Symposium on Medical Measurements and Applications … , 2018 2018 Citations: 11
Characterization of in-tunnel distance measurements for vehicle localization D Widmann, K Balać, AV Taddeo, M Prevostini, A Puiatti 2013 IEEE Wireless Communications and Networking Conference (WCNC), 2311-2316 , 2013 2013 Citations: 11
An unobtrusive fall detection system using low resolution thermal sensors and convolutional neural networks AM Rezaei, MC Stevens, A Argha, A Mascheroni, A Puiatti, NH Lovell 2021 43rd annual international conference of the IEEE Engineering in … , 2021 2021 Citations: 10
