Title: A hybrid method for classification of physical action using discrete wavelet transform and artificial neural network
Authors: Gopal Chandra Jana; Aleena Swetapadma; Prasant Kumar Pattnaik
Addresses: School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, 751024, India ' School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, 751024, India ' School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, 751024, India
Abstract: This paper proposes a method for physical action classification based on wavelet analysis and artificial neural network (ANN) from electromyography (EMG) signals. The physical action includes the person's normal action as well as aggressive action. During various types of physical actions, the EMG signals are recorded. Discrete wavelet transforms (DWT) with DB-4 wavelet is used for feature extraction from recorded EMG signals. Extracted features are given as input to the ANN-based classifier to distinguish between normal actions and aggressive actions. The hybrid approach using combination of ANN and wavelet shows significance increase in level of accuracy in classifying the physical action. Hence proposed method can be used to discriminate the physical actions ultimately helps in identifying persons mental state.
Keywords: EMG; electromyography; wavelet analysis; DWT; discrete wavelet transform; ANN; artificial neural network; classification.
International Journal of Bioinformatics Research and Applications, 2021 Vol.17 No.1, pp.25 - 37
Received: 09 May 2017
Accepted: 01 May 2018
Published online: 21 Mar 2021 *