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A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals
Ali Bashashati1, Mehrdad Fatourechi, Rabab K Ward
1Department of Electrical and Computer Engineering, The University of British Columbia, 2356 Main Mall, Vancouver, V6T 1Z4, Canada. alibs@ece.ubc.ac
Journal of Neural Engineering
|April 6, 2007
Summary
This review surveys signal processing techniques for brain-computer interfaces (BCIs) using electrical brain recordings. It identifies key components, algorithms, and popular methods in BCI research before 2006.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Signal Processing
Background:
- Brain-computer interfaces (BCIs) enable communication via brain signals.
- Effective signal processing is crucial for BCI success.
- A comprehensive review of BCI signal processing techniques is lacking.
Purpose of the Study:
- To provide the first comprehensive survey of BCI signal processing methods.
- To analyze BCI designs utilizing electrical signal recordings published before January 2006.
- To address key research questions regarding BCI signal processing components, algorithms, and trends.
Main Methods:
- Systematic literature review of BCI research.
- Analysis of signal processing techniques in published BCI studies.
- Categorization of BCI signal processing components and algorithms.
Main Results:
- Identification of core signal processing components in BCIs.
- Cataloging of various signal processing algorithms employed in BCI systems.
- Quantification of research attention towards different signal processing techniques.
Conclusions:
- The survey provides a foundational understanding of BCI signal processing up to 2006.
- Highlights the evolution and common practices in BCI signal processing.
- Informs future research directions in developing more effective BCI systems.
