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Towards Control of a Transhumeral Prosthesis with EEG Signals

System Engineering Laboratory, Department of Mechanical Engineering, Kyushu University, Fukuoka 819-0395, Japan
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Bioengineering 2018, 5(2), 26; https://doi.org/10.3390/bioengineering5020026
Received: 2 February 2018 / Revised: 19 March 2018 / Accepted: 19 March 2018 / Published: 22 March 2018
Robotic prostheses are expected to allow amputees greater freedom and mobility. However, available options to control transhumeral prostheses are reduced with increasing amputation level. In addition, for electromyography-based control of prostheses, the residual muscles alone cannot generate sufficiently different signals for accurate distal arm function. Thus, controlling a multi-degree of freedom (DoF) transhumeral prosthesis is challenging with currently available techniques. In this paper, an electroencephalogram (EEG)-based hierarchical two-stage approach is proposed to achieve multi-DoF control of a transhumeral prosthesis. In the proposed method, the motion intention for arm reaching or hand lifting is identified using classifiers trained with motion-related EEG features. For this purpose, neural network and k-nearest neighbor classifiers are used. Then, elbow motion and hand endpoint motion is estimated using a different set of neural-network-based classifiers, which are trained with motion information recorded using healthy subjects. The predictions from the classifiers are compared with residual limb motion to generate a final prediction of motion intention. This can then be used to realize multi-DoF control of a prosthesis. The experimental results show the feasibility of the proposed method for multi-DoF control of a transhumeral prosthesis. This proof of concept study was performed with healthy subjects. View Full-Text
Keywords: electroencephalography; motion intention; transhumeral prosthesis; wearable robot; brain computer interface electroencephalography; motion intention; transhumeral prosthesis; wearable robot; brain computer interface
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Bandara, D.; Arata, J.; Kiguchi, K. Towards Control of a Transhumeral Prosthesis with EEG Signals. Bioengineering 2018, 5, 26.

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