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An Approach for Brain-Controlled Prostheses Based on a Facial Expression Paradigm
Rui Li1, Xiaodong Zhang1, Zhufeng Lu1
1Shaanxi Key Laboratory of Intelligent Robot, Xi'an Jiaotong University, Xi'an, China.
Frontiers in Neuroscience
|January 9, 2019
Summary
A new brain-computer interface (BCI) system uses facial expressions to control prosthetic limbs. This novel system, the facial-expression-based BCI (FE-BCI), shows promising accuracy for advanced prosthesis control.
Area of Science:
- Neuroscience and Biomedical Engineering
- Rehabilitation Technology
Background:
- Brain-controlled prostheses translate electroencephalography (EEG) signals into commands.
- Existing brain-computer interface (BCI) methods face performance challenges.
Purpose of the Study:
- To propose and validate a novel BCI system using facial expressions for prosthesis control.
- To leverage theta and alpha rhythms from prefrontal and motor cortices for control.
Main Methods:
- Developed a facial-expression-based BCI (FE-BCI) system with a portable prosthesis.
- Utilized noise-assisted multivariate empirical mode decomposition (NA-MEMD) and sample entropy (SampEn) for artifact removal.
- Employed wavelet transform (WT) for feature extraction and a back propagation neural network (BPNN) for classification.
Main Results:
- Achieved a grand average online accuracy of 81.31 ± 5.82% across 18 subjects.
- Demonstrated the feasibility of using four distinct facial expressions for control.
- Successfully filtered electromyography (EMG) artifacts using the proposed algorithm.
Conclusions:
- The proposed FE-BCI system offers a viable and effective approach for controlling prostheses.
- Facial expression-based BCI demonstrates good performance and practical application potential in rehabilitation.
- This research addresses limitations in current BCI systems for prosthetic control.
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