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An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia
Sarcopenia is a highly prevalent, age-related muscle disorder associated with adverse outcomes. It is very important from a medical point of view to periodically monitor patients at risk of developing sarcopenia in order to early detect its onset or progression through objective and specific indicat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891689/ https://www.ncbi.nlm.nih.gov/pubmed/31739396 http://dx.doi.org/10.3390/s19224951 |
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author | Addante, Filomena Gaetani, Federico Patrono, Luigi Sancarlo, Daniele Sergi, Ilaria Vergari, Giuseppe |
author_facet | Addante, Filomena Gaetani, Federico Patrono, Luigi Sancarlo, Daniele Sergi, Ilaria Vergari, Giuseppe |
author_sort | Addante, Filomena |
collection | PubMed |
description | Sarcopenia is a highly prevalent, age-related muscle disorder associated with adverse outcomes. It is very important from a medical point of view to periodically monitor patients at risk of developing sarcopenia in order to early detect its onset or progression through objective and specific indicators. Today, the emerging Internet of Things (IoT)-enabling technologies allow us to create innovative, wearable, and non-invasive systems that can offer useful clinical support in this area. This work is focused on the use of combined hardware and software technologies, enabling the IoT, in order to monitor people suffering from sarcopenia by offering a high value-added service in the field of the Ambient Assisted Living (AAL). In addition to the description of the proposed system architecture, a validation of the entire system is also included, from both a performance and a functional point of view. Test beds have been carried out by using the independent replications method, and all measurements related to the identified sarcopenia parameters are characterized by a 95% confidence interval with a 5% maximum relative error. The implementation of these technologies as a supporting clinical tool used in a specific setting could significantly impact the life and independence of the sarcopenic frail elderly population. |
format | Online Article Text |
id | pubmed-6891689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68916892019-12-12 An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia Addante, Filomena Gaetani, Federico Patrono, Luigi Sancarlo, Daniele Sergi, Ilaria Vergari, Giuseppe Sensors (Basel) Article Sarcopenia is a highly prevalent, age-related muscle disorder associated with adverse outcomes. It is very important from a medical point of view to periodically monitor patients at risk of developing sarcopenia in order to early detect its onset or progression through objective and specific indicators. Today, the emerging Internet of Things (IoT)-enabling technologies allow us to create innovative, wearable, and non-invasive systems that can offer useful clinical support in this area. This work is focused on the use of combined hardware and software technologies, enabling the IoT, in order to monitor people suffering from sarcopenia by offering a high value-added service in the field of the Ambient Assisted Living (AAL). In addition to the description of the proposed system architecture, a validation of the entire system is also included, from both a performance and a functional point of view. Test beds have been carried out by using the independent replications method, and all measurements related to the identified sarcopenia parameters are characterized by a 95% confidence interval with a 5% maximum relative error. The implementation of these technologies as a supporting clinical tool used in a specific setting could significantly impact the life and independence of the sarcopenic frail elderly population. MDPI 2019-11-14 /pmc/articles/PMC6891689/ /pubmed/31739396 http://dx.doi.org/10.3390/s19224951 Text en © 2019 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 Addante, Filomena Gaetani, Federico Patrono, Luigi Sancarlo, Daniele Sergi, Ilaria Vergari, Giuseppe An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia |
title | An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia |
title_full | An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia |
title_fullStr | An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia |
title_full_unstemmed | An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia |
title_short | An Innovative AAL System Based on IoT Technologies for Patients with Sarcopenia |
title_sort | innovative aal system based on iot technologies for patients with sarcopenia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891689/ https://www.ncbi.nlm.nih.gov/pubmed/31739396 http://dx.doi.org/10.3390/s19224951 |
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