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All Journal Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Shankhwar, Vishwajeet
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Health Professions Materials Science & Nanotechnology

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Effect of Muscle Fatigue on Heart Signal on Physical Activity with Electromyogram and Electrocardiogram Monitoring Signals Fauzi, Muhammad; Yulianto, Endro; Irianto, Bambang Guruh; Luthfiyah, Sari; Triwiyanto, Triwiyanto; Shankhwar, Vishwajeet; Elbaghazaoui, Bahaa Eddine
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 4 No. 3 (2022): August
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v4i3.149

Abstract

Physical activity is an activity of body movement by utilizing skeletal muscles that are carried out daily. One form of physical activity is exercise which aims to improve health and fitness. Parameters related to health and wellness are heart and muscle activity. Strong and prolonged muscle contractions result in muscle fatigue. The authors used electromyographic (EMG) signals to measure muscle fatigue by monitoring changes in electrical muscle activity. This study aims to analyze the effect of muscle fatigue on cardiac signals during subjects perform 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. The authors use MPF, MDF, and MNF to get more detailed measurement results and perform a T-test. The test results showed a significant value (p-value <0.05) in the pre-test and post-test. The Pearson correlation test got a value of 0.628, indicating 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 device 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 Elbaghazaoui, Bahaa Eddine Endro Yulianto Luthfiyah, Sari Muhammad Fauzi