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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.
Afiliação
  • Kim HJ; School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea.
  • Jeong SY; Software Education Institute, Kyungpook National University, Daegu 41566, Korea.
  • Kang SJ; School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea.
Sensors (Basel) ; 22(20)2022 Oct 19.
Article em En | MEDLINE | ID: mdl-36298308
ABSTRACT
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encefalopatias / Tutoria Tipo de estudo: Qualitative_research Limite: Aged / Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encefalopatias / Tutoria Tipo de estudo: Qualitative_research Limite: Aged / Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article