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Muscle fatigue detection and treatment system driven by internet of things

Authors :
Bin Ma
Chunxiao Li
Zhaolong Wu
Yulong Huang
Ada Chaeli van der Zijp-Tan
Shaobo Tan
Dongqi Li
Ada Fong
Chandan Basetty
Glen M. Borchert
Ryan Benton
Bin Wu
Jingshan Huang
Source :
BMC Medical Informatics and Decision Making, Vol 19, Iss S7, Pp 1-9 (2019)
Publication Year :
2019
Publisher :
BMC, 2019.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
14726947
Volume :
19
Issue :
S7
Database :
Directory of Open Access Journals
Journal :
BMC Medical Informatics and Decision Making
Publication Type :
Academic Journal
Accession number :
edsdoj.0bd02c3db1164db5a1ef755be46bfa09
Document Type :
article
Full Text :
https://doi.org/10.1186/s12911-019-0982-x