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Publication Type : Conference Paper
Publisher : 2020 International Conference on Communication and Signal Processing (ICCSP),
Source : 2020 International Conference on Communication and Signal Processing (ICCSP), IEEE, Chennai, India (2020)
Campus : Amritapuri
School : School of Engineering
Department : Electronics and Communication
Year : 2020
Abstract : This research work focuses on identifying a specific hand gesture from the given EMG signal, acquired by sensor-based band. Surface EMG and machine learning techniques are used for the identification and classification purpose. The raw EMG signal captured using the sensor is initially passed through suitable preprocessing steps to avoid the noise artifacts. Followed by this, 8 different time-domain features are collected from these raw EMG signals, using which a feature matrix is created. SVM and KNN are the machine learning classifiers used here. The entire system is implemented in MATLAB 2019a. Using these methods, a promising accuracy of 93% is obtained through KNN and an accuracy of 83% using SVM.
Cite this Research Publication : Athira Devaraj and Aswathy K. Nair, “Hand Gesture Signal Classification using Machine Learning”, in 2020 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2020.