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Data Science and Engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Daphni K. Plati Fotios S. Konstantakopoulos Theofanis Kalatzis Dimitrios Manousos Thomas Kassiotis Francesco Scotto Di Luzio Nevio Luigi Tagliamonte Loredana Zollo Manolis Tsiknakis Dimitrios I. Fotiadis Materials Science and Engineering Department Unit of Medical Technology and Intelligent Information Systems University of Ioannina Biomedical Research Institute FORTH Ioannina GR 45110 Greece Institute of Computer Science FORTH Heraklion Crete GR 70013 Greece Research Unit of Advanced Robotics and Human-Centred Technologies Campus Bio-Medico University Rome Italy

Healthcare systems generally constitute a combination of healthcare facilities and providers that collaborate in order to offer a complete range of healthcare services. As the primary providers of healthcare, hospitals hold an essential place in the healthcare system. This study introduces three novel automated Artificial Intelligence (AI) systems by using the robotic platform of the TIAGo robot: (i) an image-based system that monitors the food consumption of the patients and provides information regarding their energy intake to prevent malnutrition; (ii) a rehabilitation system that monitors patients as they perform prescribed exercises to prevent loss of mobility, and (iii) a monitoring system for the correctness of the oxygen therapy in terms of the proper positioning of the oxygen mask to prevent hypoxia complications. A well-designed observational clinical study is planned to evaluate and validate the utility and effectiveness of the proposed AI systems in improving patient stay in the hospital. For the abovementioned systems, three novel datasets were *** Relevance: Through the implementation of AI systems, the proposed research intends to provide specialists with an extra tool to aid in the monitoring of hospitalized patients, thus helping to prepare the way for the Smart Hospital.

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Automated Food Intake Monitoring System to Prevent Malnutrition Using the Tiago Robot Camera*

Automated Food Intake Monitoring System to Prevent Malnutrit...

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Data Science and Engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Fotios S. Konstantakopoulos Daphni K. Plati Labrina A. Pliakou Francesco Scotto Di Luzio Nevio Luigi Tagliamonte Loredana Zollo Manolis Tsiknakis Dimitrios I. Fotiadis Unit of Medical Technology and Intelligent Information Systems Materials Science and Engineering Department University of Ioannina Biomedical Research Institute FORTH Ioannina GR 45110 Greece Research Unit of Advanced Robotics and Human-Centred Technologies Campus Bio-Medico University Rome Italy Institute of Computer Science FORTH Heraklion Crete GR 70013 Greece

The management of a daily diet is a significant concern among individuals in modern culture. The utilization of dietary assessment systems has significantly contributed to the efficient management of malnutrition and dietary habits over a period of time. In order to determine the nutritional value of the food that individuals consume, this study introduces a novel food monitoring system and its architecture. By creating a dataset of food images in a tray and using image processing, machine learning, and computer vision techniques, the nutrients and calories consumed by a patient are calculated. The proposed system achieves a 95.6% Intersection over Union score in the segmentation task, 92.3% top-1 accuracy in the classification task, and 4.6 g mean weight absolute error in the weight estimation *** Relevance: The proposed system has the ability to calculate the nutritional composition, encompassing calories, proteins, fats, and carbs, of food consumed by a patient, making it suitable for nutritional monitoring applications and healthcare systems that aim to monitor malnutrition in hospital patients.

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Biomechanics of Exoskeleton-Assisted Treadmill Walking

Biomechanics of Exoskeleton-Assisted Treadmill Walking

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IEEE International Conference on Rehabilitation robotics (ICORR)

作者： F. Di Tommaso F. Tamburella M. Lorusso L. Gastaldi M. Molinari N. L. Tagliamonte Research Unit of Advanced Robotics and Human-Centred Technologies Università Campus Bio-Medico di Roma Rome Italy Neurorehabilitation 1 Department Laboratory of Robotic Neurorehabilitation Fondazione Santa Lucia Rome Italy Department of Mechanical and Aerospace Engineering Politecnico di Torino Turin Italy

To exploit the benefits of treadmill-based exoskeletons, it is crucial to assess possible deviations from natural walking depending on assistive parameters. This study evaluated the biomechanics of exoskeleton-assisted treadmill walking by comparing it with free gait. Five healthy participants walked freely on a treadmill and with the assistance of the Lokomat gait trainer, while changing Body Weight Support (BWS), Gait Speed (GS), and Guidance Force (GF). Results showed that the hip and knee joint kinematics depended on BWS and GS, while changes due to GF were limited. Moreover, joint kinematics and the activity of related muscles were altered with respect to free gait, for any combination of robot parameters in the case of the ankle, and especially for low GS and with BWS in the case of hip and knee. Overall, walking with the Lokomat can mostly resemble free gait at high speed and without BWS.

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A human-human Physical Interaction System for Training Handwriting

A Human-Human Physical Interaction System for Training Handw...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： S. Buscaglione A. Noccaro C. Provenzale C. Bonsignori E. Ivanova L. Sparaci F. Taffoni E. Burdet D. Formica NEXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit Università Campus Bio-Medico di Roma Italy Neurorobotics Lab Newcastle University Newcastle Upon Tyne UK Advanced Robotics and Human-Centred Technologies-CREO Laboratory Università Campus Bio-Medico di Roma Italy Department of Bioengineering Imperial College of Science Technology and Medicine UK School of Electric Engineering and Computer Science Queen Mary University of London UK Institute of Cognitive Sciences and Technologies (ISTC) National Research Council of Italy (CNR) Italy

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Handwriting training in childhood is known to influence academic success, foster self-esteem, and contribute to overall development. Previous studies underscored the positive impact of haptic feedback on handwriting learning using one-way communication systems that provided the trainee with haptic feedback based on pre-recorded trainer's movements. In this study, we propose a system involving bidirectional physical coupling (haptic communication) between a trainee and a trainer to exploit the advantages of haptic communication for motor task improvement, proved in tracking tasks. The system, composed of an interactive display and a coupling spring, was tested in a handwriting task performed by a dyad of healthy adults with different cursive handwriting backgrounds. The participants' performance demonstrated the feasibility of using this system for handwriting, opening the way for further studies to assess its benefits in handwriting improvement and learning.

关键词： Training Couplings Tracking Communication systems Biomechatronics Motors Haptic interfaces Springs Robots

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Deep Learning for human Locomotion Analysis in Lower-Limb Exoskeletons: A Comparative Study

arXiv

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arXiv 2025年

作者： Coser, Omar Tamantini, Christian Tortora, Matteo Furia, Leonardo Sicilia, Rosa Zollo, Loredana Soda, Paolo Unit of Computer Systems & Bioinformatics Università Campus Bio-Medico di Roma Via Álvaro del Portillo 21 Rome00128 Italy Unit of Advanced Robotics and Human-Centered Technologies Università Campus Bio-Medico di Roma Via Álvaro del Portillo 21 Rome00128 Italy Dipartimento di Ingegneria Navale Elettrica Elettronica e delle Telecomunicazioni Università degli Studi di Genova Via all’Opera Pia 11a Genova16145 Italy Department of Diagnostics and Intervention Radiation Physics Biomedical Engineering Umeå University Universitetstorget 4 Umeå40196 Sweden Institute of Cognitive Sciences and Technologies National Research Council of Italy Rome00196 Italy

Wearable robotics for lower-limb assistance have become a pivotal area of research, aiming to enhance mobility for individuals with physical impairments or augment the performance of able-bodied users. Accurate and adaptive control systems are essential to ensure seamless interaction between the wearer and the robotic device, particularly when navigating diverse and dynamic terrains. Despite the recent advances in neural networks for time series analysis, no attempts have been directed towards the classification of ground conditions, categorized into five classes and subsequently determining the ramp’s slope and stair’s height. In this respect, this paper presents an experimental comparison between eight deep neural network backbones to predict high-level locomotion parameters across diverse terrains. All the models are trained on the publicly available CAMARGO 2021 dataset. IMU-only data equally or outperformed IMU+EMG inputs, promoting a cost-effective and efficient design. Indeeds, using three IMU sensors, the LSTM achieved high terrain classification accuracy (0.94 ± 0.04) and precise ramp slope (1.95 ± 0.58°) and the CNN-LSTM a stair height (15.65 ± 7.40 mm) estimations. As a further contribution, SHAP analysis justified sensor reduction without performance loss, ensuring a lightweight setup. The system operates with 2 ms inference time, supporting real-time applications. The code is code available at https://***/cosbidev/human-Locomotion-Identification. © 2025, CC BY.

关键词： Adaptive control systems

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Estimation of the metabolic rate in the occupational field: a regression model using accelerometers

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International Journal of Industrial Ergonomics 2023年第1期96卷

作者： Falcone, Tiziana Del Ferraro, Simona Molinaro, Vincenzo Zollo, Loredana Lenzuni, Paolo Laboratory of Ergonomics and Physiology Department of Occupational and Environmental Medicine Epidemiology and Hygiene INAIL via Fontana Candida 1 Monte Porzio Catone Rome Italy Unit of Advanced Robotics and Human-Centred Technologies Campus Bio-Medico University of Rome via Álvaro del Portillo 200 Rome Italy Tuscany Regional Research Center INAIL Florence Italy

The aim of this study is to investigate the ability of the acceleration vector magnitude (VM) to predict the metabolic rate (M) for a variety of work activities. Accurate knowledge of M is of vital importance to evaluate the energy cost of work activity. While precise estimates of M can be achieved using direct calorimetry, this is not a viable option in workplaces. Ten healthy subjects (5 males, 5 females) were enrolled in six tasks simulating specific work activities. During each test, oxygen consumption rate (V˙O2), carbon dioxide production rate (V˙CO2) and accelerations at three body positions were measured. V˙O2 and V˙CO2 were used to obtain M and accelerations to calculate VM. Three mono-linear zero-intercept regression models based on center-of-mass VM were developed. A zero-intercept functional relation between M and VM was applied to the whole data set yielding the Global model. A R2 of 0.30 was obtained which indicates limited predictive ability. Two other (Vertical and Horizontal) models were also developed by separating tasks with different kinematics. With R2 = 0.56 and 0.61 they represent a significant improvement over the Global model. The results reveal a low R2 for the Global model due to collecting in the same sample many tasks that have little in common. A large R2 improvement is achieved when the dominant direction of movement is considered. The proposed method is based on a non-invasive easy-to-measure physiological parameter and can be used to track the activity level during work activity in the industrial sector. © 2023 Elsevier B.V.

关键词： Carbon dioxide

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Study of Parametric Effects due to Mutual Coupling using High Permittivity Dielectric-Director in Planar Array Configuration 7

Study of Parametric Effects due to Mutual Coupling using Hig...

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7th IEEE International Conference on Engineering technologies and Applied Sciences, ICETAS 2020

作者： Shaikh, Faraz Ahmed Khan, Sheroz Alvi, Bilal Ahmad Alam, Ahm Zahirul Baillargeat, Dominique Joyo, M. Kamran Faculty of Eng Dept. of Electrical Eng Karachi Pakistan Onaizah Colleges of Engineering Electronics Renewable Eng Dept. of Electrical Saudi Arabia Faculty of Eng Dept. of ECE Kuala Lumpur Malaysia XLIM University of Limoges Dept. of Research Limoges France Università Campus Bio-Medico di Unit of Advanced Robotics and Human-centred Technologies Roma Italy

ISBN: (纸本)9780738105048

This paper evaluate the parametric effects due to mutual coupling between inter-elements using balance antipodal Vivaldi antenna (BAVA) with high permittivity dielectric director in an array configuration. An elliptical shaped dielectric-director made by the substrate of Rogers RO-3010 with high permittivity of ϵr=10.2 is used with BAVA in order to enhance the radiation characteristics of the antenna in focus. An antenna (66mm × 60.75mm) in dimension designed on FR4 substrate, which covers ultra-wide frequency band of 114.28% from 3GHz to 8GHz. The performance of an antenna with dielectric director is evaluated in a capacity of gain enhancement, directivity, regular radiation pattern with low side lobe level and beam width. Further, the use of dielectric directors in planner antenna array based configuration can provide significantly change in radiation characteristic and also provide help in the reduction of mutual coupling inter-elements. The same results can be obtained by using four elements with high permittivity dielectric directors in the planner antenna array based arrangement instead of eight or more elements without directors. This is an alternative way to reduce the number of elements in an antenna array based system. The design and optimization progression is realized out using CST simulation software. © 2020 IEEE.

关键词： Antenna arrays

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Design and development of an instrumented glove for hand rehabilitation in children suffering from cerebral palsy: a digital manufacturing approach

Design and development of an instrumented glove for hand reh...

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Workshop on Metrology for Industry 4.0 and IoT

作者： Giorgia Cusimano Alessia Longo Alessio Uffreduzzi Marco Bravi Fabrizio Taffoni Advanced Robotics and Human-Centred Technologies - CREO Lab Università Campus Bio-Medico di Roma Rome Italy Physical Medicine and Rehabilitation Research Unit Università Campus Bio-Medico di Roma Rome Italy

ISBN: (数字)9781728148922

ISBN: (纸本)9781728148939

Cerebral palsy in infancy represents one of the major causes of permanent motor deficit in the upper limb movements. An early diagnosis and timely rehabilitation therapy would facilitate the partial or total recovery of the physiological movement range. Unfortunately, currently available technological solutions for rehabilitation and assessment of upper limb are not suited for children younger than 5 years of age. The advancements in manufacturing technologies have made possible the fabrication of highly accurate custom physical models of patient anatomy and, more recently, patient specific implants. This work investigates the possibility to develop a workflow based on digital manufacturing technologies to design parametric solutions for rehabilitation and motor assessment in children younger than 5 years of age. In details, this work presents the development of an instrumented glove for the assessment of thumb therapy in children aged between 4 and 5 years suffering from the “thumb in the palm syndrome”.

关键词： smart glove digital manufacturing personalized therapy Digital manufacturing Manufacturing technology Rehabilitation Cerebral Palsy Child Gloves Upper Extremity Thumb rehabilitation therapy Lake Restoration

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WE-184. From “irritative zone” to “irritative network”: a novel interictal estimate of the epileptogenic zone using invasive EEG

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Clinical Neurophysiology 2022年 141卷 S86-S86页

作者： Pesce, Matthew Billardello, Roberto Pace, Lavinia Madsen, Joseph Pearl, Phillip Papadelis, Christos Grant, Ellen Tamilia, Eleonora Fetal-Neonatal Neuroimaging and Developmental Science Center Boston Children's Hospital Boston USA Research Unit of Advanced Robotics and Human-Centered Technologies Department of Engineering University Bio-Medico Campus of Rome Rome Italy Epilepsy Surgery Program Department of Neurosurgery Boston Children’s Hospital Boston USA Harvard Medical School Boston USA Division of Epilepsy and Clinical Neurophysiology Department of Neurology Boston Children’s Hospital Boston USA Jane and John Justin Neurosciences Center Cook Children’s Health Care System Fort Worth USA Department of Bioengineering University of Texas at Arlington Arlington USA Fetal-Neonatal Neuroimaging and Developmental Science Center Boston Children’s Hospital Boston USA

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WE-173. Combining excitability and connectivity measures from interictal invasive-EEG estimates the epileptogenic zone, even in the absence of frank epileptiform activity

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Clinical Neurophysiology 2022年 141卷 S81-S82页

作者： Billardello, Roberto Ntolkeras, Georgios Pesce, Matthew Harmon, Joseph Hadjinicolaou, Aristides Madsen, Joseph Taffoni, Fabrizio Pearl, Phillip Papadelis, Christos Grant, Ellen Tamilia, Eleonora Fetal-Neonatal Neuroimaging and Developmental Science Center Boston Children’s Hospital Harvard Medical School Boston USA Research Unit of Advanced Robotics and Human-Centred Technologies Department of Engineering University Bio-Medico Campus of Rome Rome Italy Baystate Children's Hospital Springfield USA Division of Epilepsy and Clinical Neurophysiology Department of Neurology Boston Children’s Hospital Harvard Medical School Boston USA Epilepsy Surgery Program Department of Neurosurgery Boston Children’s Hospital Harvard Medical School Boston USA Jane and John Justin Neurosciences Center Cook Children’s Health Care System Fort Worth USA Department of Bioengineering University of Texas at Arlington Arlington USA

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