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ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases
Technology advancements in wireless communication and embedded computing are fostering their evolution from standalone elements to smart objects seamlessly integrated in the broader context of the Internet of Things. In this context, wearable sensors represent the building block for new cyber-physic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339172/ https://www.ncbi.nlm.nih.gov/pubmed/30577467 http://dx.doi.org/10.3390/s19010002 |
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author | Vallati, Carlo Virdis, Antonio Gesi, Marco Carbonaro, Nicola Tognetti, Alessandro |
author_facet | Vallati, Carlo Virdis, Antonio Gesi, Marco Carbonaro, Nicola Tognetti, Alessandro |
author_sort | Vallati, Carlo |
collection | PubMed |
description | Technology advancements in wireless communication and embedded computing are fostering their evolution from standalone elements to smart objects seamlessly integrated in the broader context of the Internet of Things. In this context, wearable sensors represent the building block for new cyber-physical social systems, which aim at improving the well-being of people by monitoring and measuring their activities and provide an immediate feedback to the users. In this paper, we introduce ePhysio, a large-scale and flexible platform for sensor-assisted physiotherapy and remote management of musculoskeletal diseases. The system leverages networking and computing tools to provide real-time and ubiquitous monitoring of patients. We propose three use cases which differ in scale and context and are characterized by different human interactions: single-user therapy, indoor group therapy, and on-field therapy. For each use case, we identify the social interactions, e.g., between the patient and the physician and between different users and the performance requirements in terms of monitoring frequency, communication, and computation. We then propose three related deployments, highlighting the technologies that can be applied in a real system. Finally, we describe a proof-of-concept implementation, which demonstrates the feasibility of the proposed solution. |
format | Online Article Text |
id | pubmed-6339172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63391722019-01-23 ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases Vallati, Carlo Virdis, Antonio Gesi, Marco Carbonaro, Nicola Tognetti, Alessandro Sensors (Basel) Article Technology advancements in wireless communication and embedded computing are fostering their evolution from standalone elements to smart objects seamlessly integrated in the broader context of the Internet of Things. In this context, wearable sensors represent the building block for new cyber-physical social systems, which aim at improving the well-being of people by monitoring and measuring their activities and provide an immediate feedback to the users. In this paper, we introduce ePhysio, a large-scale and flexible platform for sensor-assisted physiotherapy and remote management of musculoskeletal diseases. The system leverages networking and computing tools to provide real-time and ubiquitous monitoring of patients. We propose three use cases which differ in scale and context and are characterized by different human interactions: single-user therapy, indoor group therapy, and on-field therapy. For each use case, we identify the social interactions, e.g., between the patient and the physician and between different users and the performance requirements in terms of monitoring frequency, communication, and computation. We then propose three related deployments, highlighting the technologies that can be applied in a real system. Finally, we describe a proof-of-concept implementation, which demonstrates the feasibility of the proposed solution. MDPI 2018-12-20 /pmc/articles/PMC6339172/ /pubmed/30577467 http://dx.doi.org/10.3390/s19010002 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vallati, Carlo Virdis, Antonio Gesi, Marco Carbonaro, Nicola Tognetti, Alessandro ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases |
title | ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases |
title_full | ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases |
title_fullStr | ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases |
title_full_unstemmed | ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases |
title_short | ePhysio: A Wearables-Enabled Platform for the Remote Management of Musculoskeletal Diseases |
title_sort | ephysio: a wearables-enabled platform for the remote management of musculoskeletal diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339172/ https://www.ncbi.nlm.nih.gov/pubmed/30577467 http://dx.doi.org/10.3390/s19010002 |
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