EMG denoising and feature optimization for forearm movement classification

Surface electromyography (sEMG) signal is one of the most significant biomedical signals that are widely applied in both medical and engineering applications. As many disabled and elder people have difficulty accessing current assistive devices which have a traditional user interface, such as joysticks and keyboards, more advanced hands-free human-machine interfaces (HMIs) are necessary. The study presented in this thesis was aimed to use the sEMG signals during upper-limb movements from the forearm muscles for the control of assistive devices, as known the multifunction myoelectric control system. Four main components have been more carefully considered. Firstly, pre-processing stage based on wavelet denoising algorithms was evaluated and the optimal parameters were presented. The system with this pre-processing stage improved both classification accuracy and robustness. Secondly, existing EMG feature extraction methods were evaluated and new EMG features based on fractal analysis were proposed. The optimal feature vector which consists of time-domain features i.e. Willison amplitude, waveform length and root mean square, as well as fractal features i.e. detrended fluctuation analysis and critical exponent analysis was suggested. Thirdly, the use of extended versions of linear discriminant analysis (LDA) method i.e. uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis were not only reducing the computational time but also increasing the accuracy of the system. Finally, the LDA classifier was used due to a robustness property. In this study, the proposed systems not only improve the classification accuracy but also increase the robustness and decrease the complexity. The major applications of the proposed systems are prosthesis and electric power wheelchair. Recent and future trends of both applications have also been presented. ชื อวิทยานพินธ ์ การลดสญัญาณรบกวนในสญัญาณไฟฟ้ากล้ามเนื อ และการหาลักษณะ เด่นที เหมาะสม สาํหรับการจาํแนกรูปแบบการเคลื อนไหวของแขน ทอ่นล่าง ผูเ้ขียน นายองักูร ภิญโญมารค สาขาวิชา วิศวกรรมไฟฟ้า ปีการศึกษา 2554