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All Journal Indonesian Journal of electronics, electromedical engineering, and medical informatics
Muhammad Tariq Sadiq
School of Architecture, Technology, and Engineering, University of Brighton, United Kingdom
Computer Science & IT Control & Systems Engineering Engineering

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Detection Signal Electromyograpy using Dry Electrode and Disposible Electrodes on the Upper Extremity when Lifting Weights Farid Amrinsani; Levana Forra Wakidi; Made Dwi Pandya Suryanta; Dessy Tri Wulandari; Muhammad Tariq Sadiq
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 4 (2022): November
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.v4i4.252

Abstract

One of the biosignals used to identify human muscle impulses is electromyography. Electromyographic signals are frequently utilized as inputs and are designed to help persons with disabilities or aid in the healing process following stroke therapy. According to studies, this occurrence has led to the development of numerous electromyography module sensor designs to meet different purposes. In this work, disposable electrodes and dry electrodes are used to examine the root mean square RMS values of two different electromyography sensor module types. With a 3 kg barber lift action, each module is used to detect signals in the biceps, which are part of the upper extremity muscles. According to the study's findings, the two electromyography modules with disposable electrodes produced data with a p-value of 0.001766368 0.05. It can be inferred that there is no difference between the E1 and E2 modules because the p-value for the t-test of the two modules with dry electrodes is 0.001766368 0.05. However, there is a variance in the amplitude's magnitude, with a difference of 30mV between the disposable and dry electrodes. The results of this study can be used to teach students, and a module developed as a result of it can be applied to other studies to help find electromyographic signals.
Co-Authors Dessy Tri Wulandari Farid Amrinsani Levana Forra Wakidi Made Dwi Pandya Suryanta