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All Journal Indonesian Journal of electronics, electromedical engineering, and medical informatics
Bahaa Eddine ELBAGHAZAOUI
IBN tofail University, Morocco
Computer Science & IT Control & Systems Engineering Engineering

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Effect of Muscle Fatigue on Heart Signal on Physical Activity with Electromyogram and Electrocardiogram (EMG Parameter ) Monitoring Signals Muhammad Fauzi; Endro Yulianto; Bambang Guruh Irianto; Sari Luthfiyah; Triwiyanto Triwiyanto; Vishwajeet Shankhwar; Bahaa Eddine ELBAGHAZAOUI
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 3 (2022): August
Publisher : Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v4i3.240

Abstract

Physical activity is an activity of body movement by utilizing skeletal muscles that is carried out daily. One form of physical activity is an exercise that aims to improve health and fitness. Parameters related to health and fitness are heart and muscle activity. Strong and prolonged muscle contractions result in muscle fatigue. To measure muscle fatigue, the authors used electromyographic (EMG) signals through monitoring changes in muscle electrical activity. This study aims to make a tool to detect the effect of muscle fatigue on cardiac signals on physical activity. This research method uses Fast Fourier Transform (FFT) with one group pre-test-post-test research design. The independent variable is the EMG signal when doing plank activities, while the dependent variable is the result of monitoring the EMG signal. To get more detailed measurement results, the authors use MPF, MDF and MNF and perform a T-test. The test results showed a significant value (pValue <0.05) in the pre-test and post-test. The Pearson correlation test got a value of 0.628 which indicates there is a strong relationship between exercise frequency and plank duration. When the respondent experiences muscle fatigue, the heart signal is affected by noise movement artifacts that appear when doing the plank. It is concluded that the tools in this study can be used properly. To overcome noise in the EMG signal, it is recommended to use dry electrodes and high-quality components. To improve the ability to transmit data, it is recommended to use a Raspberry microcontroller.
Co-Authors Bambang Guruh Irianto Endro Yulianto Luthfiyah, Sari Muhammad Fauzi Triwiyanto Triwiyanto Vishwajeet Shankhwar