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Dynamic feature for an effective elbow-joint angle estimation based on electromyography signals Triwiyanto, Triwiyanto; Rahmawati, Triana; Yulianto, Endro; Mak'ruf, Muhammad Ridha; Nugraha, Priyambada Cahya
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp178-187


Some physical parameters influence the electromyography signal (EMG). when the EMG signal is used to estimate the position of the elbow. An adaptable feature was important to reduce a variation on the parameters. The aim of this paper is to estimate the joint position of the elbow using EMG signal based on a dynamic function. The major contribution of this work is that the method proposed is capable of determining the elbow position using the non-pattern (NPR) recognition (PR) method. A Wilson amplitude (WAMP) which used a dynamic threshold was used to reduce the EMG signal. The dynamic threshold was generated from the root mean square (RMS) processor. With the dynamic threshold, the model could adapt to any variations on the independent variables. In order to confirm this opportunity, this work involved ten healthy male subjects to perform an experimental protocol. After a tuning and calibration process, the mean of RMS error and correlation coefficient are 9.83º±1.69º and 0.98±0.01 for a single cycle of motion, 10.39º±1.82º and 0.97±0.01 for a continuous cycle of motion and 15.19º±1.92º and 0.94±0.02 for the arbitrary gesture. For conclusion, the performance of the prediction did not significantly depend on the varying cycle of gesture (p-value>0.05). This study has confirmed that the success of the non-pattern recognition-based prediction of elbow position is adaptable to any different subjects, loads, and speed of motion.
Digital ECG Phantom Design to Represent the Human Heart Signal for Early Test on ECG Machine in Hospital Ardila, Sella Octa; Yulianto, Endro; Sumber, Sumber
International Journal of Advanced Health Science and Technology Vol. 1 No. 1 (2021): November
Publisher : Forum Ilmiah Teknologi dan Ilmu Kesehatan (FORITIKES)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (663.633 KB) | DOI: 10.35882/ijahst.v1i1.3


Electrocardiograph (ECG) is a diagnostic tool that can record the electrical activity of the human heart. By analyzing the resulting waveforms of the recorded electrical activity of the heart, it is possible to record and diagnose disease. Given the importance of the ECG recording device, it is necessary to check the function of the ECG recording device, namely by performing a device calibration procedure using the Phantom ECG which aims to simulate the ECG signal. The purpose of this research is to check the ECG device during repairs, besides that the Electrocardiograph (EKG) tool functions for research purposes on ECG signals or for educational purposes. Electrocardiograph (EKG) simulator or often called Phantom ECG is in principle a signal generator in the form of an ECG like signal or a recorded ECG signal. This device can be realized based on microcontroller and analog circuit. The advantage of this simulator research is that the ECG signal displayed is the original ECG recording and has an adequate ECG signal database. ECG This simulator also has the advantage of providing convenience for research on digital signal processing applications for ECG signal processing. In its application this simulator can be used as a tool to study various forms of  ECG signals. Based on the measurement results, the error value at BPM 30 and 60 is 0.00% at the sensitivity of 0.5mV, 1.0mV, and 2.0mV, then the measurement results for the error value at BPM 120 are 0.33% and at the BPM 180 value, the error value is 0.22%. From these results, it can be concluded that the highest error value is at BPM 120 with sensitivities of 0.5mV, 1.0mV, and 2.0mV.