Gym training muscle fatigue monitoring using EMG myoware and arduino with envelope and sliding window methods

Sena Sukmananda Suprapto, Vicky Andria Kusuma, Mifta Nur Farid, Muhammad Agung Nursyeha, Kharis Sugiarto, Aji Akbar Firdaus, Dimas Fajar Uman Putra

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Muscles are an important organ in the movement of the body's skeleton to carry out sports activities. Measurement of muscle activity during the exercise process can be done using electromyography (EMG). This research uses Myoware muscle sensor (AT-04-001) which is integrated with Arduino Uno and Xbee to monitor biceps brachii muscle fatigue wirelessly. Fatigue data processing is carried out objectively using the envelope and sliding window method and subjectively verbally from the respondents. From this study, it was found that muscle fatigue can be measured using the method objectively when there is an increase in EMG amplitude with a window size of 5 s. The indication of biceps brachii muscle fatigue for the right arm is stronger to withstand the load during exercise with the average duration of the measurement of the right arm is 41.87 s from 69.67 s; 53.53 s from 98.90 s and 76.87 s from 98.80 s with the ratio of the left arm tending to fatigue more quickly is 23.53 s from 42.13 s; 41.87 s from 51.60 s and 23.53 s from 44.73 s.

Original languageEnglish
Pages (from-to)345-350
Number of pages6
JournalInternational Journal of Reconfigurable and Embedded Systems
Volume12
Issue number3
DOIs
Publication statusPublished - Nov 2023

Keywords

  • Arduino uno
  • Electromyography
  • Envelope
  • Gym
  • Sliding window method

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