Research Article
Discrete Wavelet and Neural Network Algorithm for Real-time Identification Finger Movement
@INPROCEEDINGS{10.4108/eai.7-11-2023.2342938, author={Sumantri Kurniawan Risandrya and Edo Putra Sinaga and Daniel Sutopo Pamungkas}, title={Discrete Wavelet and Neural Network Algorithm for Real-time Identification Finger Movement }, proceedings={Proceedings of the 6th International Conference on Applied Engineering, ICAE 2023, 7 November 2023, Batam, Riau islands, Indonesia}, publisher={EAI}, proceedings_a={ICAE}, year={2024}, month={1}, keywords={emg discrete wavelet neural network identification}, doi={10.4108/eai.7-11-2023.2342938} }- Sumantri Kurniawan Risandrya
Edo Putra Sinaga
Daniel Sutopo Pamungkas
Year: 2024
Discrete Wavelet and Neural Network Algorithm for Real-time Identification Finger Movement
ICAE
EAI
DOI: 10.4108/eai.7-11-2023.2342938
Abstract
Electromyography (EMG) Signals from human muscles can be utilized in various fields. One of them is in the control field. Some control systems use a person's finger movements. So, an algorithm is needed to recognize hand movement patterns. This paper examines systems' capabilities using neural network algorithms with discrete wavelet transforms. The signal is obtained from the EMG signal generated by the surface EMG sensor. This sensor is issued on the user's upper arm. This study used three healthy subjects with five-finger movements. This system is able to recognize patterns of finger movements, about 79.79%.
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