Towards control of a transhumeral prosthesis with EEG signals

27Citations
Citations of this article
66Readers
Mendeley users who have this article in their library.

Abstract

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.

References Powered by Scopus

Event-related EEG/MEG synchronization and desynchronization: Basic principles

5748Citations
N/AReaders
Get full text

Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms

879Citations
N/AReaders
Get full text

Electrocorticograms in man: Effect of voluntary movement upon the electrical activity of the precentral gyrus

505Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Real-time EMG based pattern recognition control for hand prostheses: A review on existing methods, challenges and future implementation

243Citations
N/AReaders
Get full text

Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces

40Citations
N/AReaders
Get full text

EEG Channel Selection Techniques in Motor Imagery Applications: A Review and New Perspectives

29Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Bandara, D. S. V., Arata, J., & Kiguchi, K. (2018). Towards control of a transhumeral prosthesis with EEG signals. Bioengineering, 5(2). https://doi.org/10.3390/bioengineering5020026

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 28

76%

Researcher 4

11%

Lecturer / Post doc 3

8%

Professor / Associate Prof. 2

5%

Readers' Discipline

Tooltip

Engineering 31

72%

Medicine and Dentistry 7

16%

Chemistry 3

7%

Biochemistry, Genetics and Molecular Bi... 2

5%

Article Metrics

Tooltip
Mentions
Blog Mentions: 1

Save time finding and organizing research with Mendeley

Sign up for free