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While there are a number of different health-related problems encountered in daily life, muscle fatigue is a common problem encountered by many.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Methods<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Results<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Discussion<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Conclusions<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>","DOI":"10.1186\/s12911-019-0982-x","type":"journal-article","created":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T01:02:30Z","timestamp":1577062950000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Muscle fatigue detection and treatment system driven by internet of things"],"prefix":"10.1186","volume":"19","author":[{"given":"Bin","family":"Ma","sequence":"first","affiliation":[]},{"given":"Chunxiao","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhaolong","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Yulong","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Ada Chaeli","family":"van der Zijp-Tan","sequence":"additional","affiliation":[]},{"given":"Shaobo","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Dongqi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Ada","family":"Fong","sequence":"additional","affiliation":[]},{"given":"Chandan","family":"Basetty","sequence":"additional","affiliation":[]},{"given":"Glen M.","family":"Borchert","sequence":"additional","affiliation":[]},{"given":"Ryan","family":"Benton","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Jingshan","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,12,23]]},"reference":[{"issue":"08","key":"982_CR1","first-page":"80","volume":"39","author":"Z Liu","year":"2008","unstructured":"Liu Z, Shu M, Kong X, Shan K, Zhao K. 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