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Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients

The activities of daily living (ADL) ability level of an elderly patient is an important indicator in determining the patient’s degree of degenerative brain disease and is mainly evaluated through face-to-face interviews with doctors and patients in hospitals. It is impossible to determine the exact...

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Autores principales: Kim, Hyo-Jung, Jeong, Seol-Young, Kang, Soon-Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612111/
https://www.ncbi.nlm.nih.gov/pubmed/36298308
http://dx.doi.org/10.3390/s22207957
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author Kim, Hyo-Jung
Jeong, Seol-Young
Kang, Soon-Ju
author_facet Kim, Hyo-Jung
Jeong, Seol-Young
Kang, Soon-Ju
author_sort Kim, Hyo-Jung
collection PubMed
description The activities of daily living (ADL) ability level of an elderly patient is an important indicator in determining the patient’s degree of degenerative brain disease and is mainly evaluated through face-to-face interviews with doctors and patients in hospitals. It is impossible to determine the exact ADL ability of a patient through such a temporary interview, and the pursuit of accurate ADL ability evaluation technology is a very important research task worldwide. In this paper, in order to overcome the limitations of the existing ADL evaluation method mentioned above, first of all, a self-organized IoT architecture in which IoT devices autonomously and non-invasively measure a patient’s ADL ability within the context of the patient’s daily living place was designed and implemented. Second, a remote rehabilitation treatment concept for enhancing the patient’s ADL ability we call an “e-coaching framework”, in which a doctor remotely gives an instruction in a specific ADL scenario, and the patient’s ability to understand and perform the instruction can be measured on-line and in real time, was additionally developed on top of the self-organized IoT architecture. In order to verify the possibility of remote rehabilitation treatment through the proposed architecture, various remotely directed ADL scenarios were performed and the accuracy of the measurements was verified.
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spelling pubmed-96121112022-10-28 Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients Kim, Hyo-Jung Jeong, Seol-Young Kang, Soon-Ju Sensors (Basel) Article The activities of daily living (ADL) ability level of an elderly patient is an important indicator in determining the patient’s degree of degenerative brain disease and is mainly evaluated through face-to-face interviews with doctors and patients in hospitals. It is impossible to determine the exact ADL ability of a patient through such a temporary interview, and the pursuit of accurate ADL ability evaluation technology is a very important research task worldwide. In this paper, in order to overcome the limitations of the existing ADL evaluation method mentioned above, first of all, a self-organized IoT architecture in which IoT devices autonomously and non-invasively measure a patient’s ADL ability within the context of the patient’s daily living place was designed and implemented. Second, a remote rehabilitation treatment concept for enhancing the patient’s ADL ability we call an “e-coaching framework”, in which a doctor remotely gives an instruction in a specific ADL scenario, and the patient’s ability to understand and perform the instruction can be measured on-line and in real time, was additionally developed on top of the self-organized IoT architecture. In order to verify the possibility of remote rehabilitation treatment through the proposed architecture, various remotely directed ADL scenarios were performed and the accuracy of the measurements was verified. MDPI 2022-10-19 /pmc/articles/PMC9612111/ /pubmed/36298308 http://dx.doi.org/10.3390/s22207957 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Hyo-Jung
Jeong, Seol-Young
Kang, Soon-Ju
Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients
title Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients
title_full Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients
title_fullStr Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients
title_full_unstemmed Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients
title_short Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients
title_sort knowledge-based remote e-coaching framework using iot devices for in-home adl rehabilitation treatment of degenerative brain disease patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612111/
https://www.ncbi.nlm.nih.gov/pubmed/36298308
http://dx.doi.org/10.3390/s22207957
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