Cargando…

Muscle fatigue detection and treatment system driven by internet of things

BACKGROUND: Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. While there are a number of different health-related problems encountered in daily...

Descripción completa

Detalles Bibliográficos
Autores principales: Ma, Bin, Li, Chunxiao, Wu, Zhaolong, Huang, Yulong, van der Zijp-Tan, Ada Chaeli, Tan, Shaobo, Li, Dongqi, Fong, Ada, Basetty, Chandan, Borchert, Glen M., Benton, Ryan, Wu, Bin, Huang, Jingshan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927109/
https://www.ncbi.nlm.nih.gov/pubmed/31865898
http://dx.doi.org/10.1186/s12911-019-0982-x
_version_ 1783482241436876800
author Ma, Bin
Li, Chunxiao
Wu, Zhaolong
Huang, Yulong
van der Zijp-Tan, Ada Chaeli
Tan, Shaobo
Li, Dongqi
Fong, Ada
Basetty, Chandan
Borchert, Glen M.
Benton, Ryan
Wu, Bin
Huang, Jingshan
author_facet Ma, Bin
Li, Chunxiao
Wu, Zhaolong
Huang, Yulong
van der Zijp-Tan, Ada Chaeli
Tan, Shaobo
Li, Dongqi
Fong, Ada
Basetty, Chandan
Borchert, Glen M.
Benton, Ryan
Wu, Bin
Huang, Jingshan
author_sort Ma, Bin
collection PubMed
description BACKGROUND: Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. While there are a number of different health-related problems encountered in daily life, muscle fatigue is a common problem encountered by many. METHODS: To facilitate muscle fatigue detection, a pulse width modulation (PWM) and ESP8266-based fatigue detection and recovery system is introduced in this paper to help alleviate muscle fatigue. The ESP8266 is employed as the main controller and communicator, and PWM technology is employed to achieve adaptive muscle recovery. Muscle fatigue can be detected by surface electromyography signals and monitored in real-time via a wireless network. RESULTS: With the help of the proposed system, human muscle fatigue status can be monitored in real-time, and the recovery vibration motor status can be optimized according to muscle activity state. DISCUSSION: Environmental factors had little effect on the response time and accuracy of the system, and the response time was stable between 1 and 2 s. As indicated by the consistent change of digital value, muscle fatigue was clearly diminished using this system. CONCLUSIONS: Experiments show that environmental factors have little effect on the response time and accuracy of the system. The response time is stably between 1 and 2 s, and, as indicated by the consistent change of digital value, our systems clearly diminishes muscle fatigue. Additionally, the experimental results show that the proposed system requires minimal power and is both sensitive and stable.
format Online
Article
Text
id pubmed-6927109
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-69271092019-12-30 Muscle fatigue detection and treatment system driven by internet of things Ma, Bin Li, Chunxiao Wu, Zhaolong Huang, Yulong van der Zijp-Tan, Ada Chaeli Tan, Shaobo Li, Dongqi Fong, Ada Basetty, Chandan Borchert, Glen M. Benton, Ryan Wu, Bin Huang, Jingshan BMC Med Inform Decis Mak Research BACKGROUND: Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. While there are a number of different health-related problems encountered in daily life, muscle fatigue is a common problem encountered by many. METHODS: To facilitate muscle fatigue detection, a pulse width modulation (PWM) and ESP8266-based fatigue detection and recovery system is introduced in this paper to help alleviate muscle fatigue. The ESP8266 is employed as the main controller and communicator, and PWM technology is employed to achieve adaptive muscle recovery. Muscle fatigue can be detected by surface electromyography signals and monitored in real-time via a wireless network. RESULTS: With the help of the proposed system, human muscle fatigue status can be monitored in real-time, and the recovery vibration motor status can be optimized according to muscle activity state. DISCUSSION: Environmental factors had little effect on the response time and accuracy of the system, and the response time was stable between 1 and 2 s. As indicated by the consistent change of digital value, muscle fatigue was clearly diminished using this system. CONCLUSIONS: Experiments show that environmental factors have little effect on the response time and accuracy of the system. The response time is stably between 1 and 2 s, and, as indicated by the consistent change of digital value, our systems clearly diminishes muscle fatigue. Additionally, the experimental results show that the proposed system requires minimal power and is both sensitive and stable. BioMed Central 2019-12-23 /pmc/articles/PMC6927109/ /pubmed/31865898 http://dx.doi.org/10.1186/s12911-019-0982-x Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Ma, Bin
Li, Chunxiao
Wu, Zhaolong
Huang, Yulong
van der Zijp-Tan, Ada Chaeli
Tan, Shaobo
Li, Dongqi
Fong, Ada
Basetty, Chandan
Borchert, Glen M.
Benton, Ryan
Wu, Bin
Huang, Jingshan
Muscle fatigue detection and treatment system driven by internet of things
title Muscle fatigue detection and treatment system driven by internet of things
title_full Muscle fatigue detection and treatment system driven by internet of things
title_fullStr Muscle fatigue detection and treatment system driven by internet of things
title_full_unstemmed Muscle fatigue detection and treatment system driven by internet of things
title_short Muscle fatigue detection and treatment system driven by internet of things
title_sort muscle fatigue detection and treatment system driven by internet of things
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927109/
https://www.ncbi.nlm.nih.gov/pubmed/31865898
http://dx.doi.org/10.1186/s12911-019-0982-x
work_keys_str_mv AT mabin musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT lichunxiao musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT wuzhaolong musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT huangyulong musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT vanderzijptanadachaeli musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT tanshaobo musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT lidongqi musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT fongada musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT basettychandan musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT borchertglenm musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT bentonryan musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT wubin musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings
AT huangjingshan musclefatiguedetectionandtreatmentsystemdrivenbyinternetofthings