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Non-motor tasks improve adaptive brain-computer interface performance in users with severe motor impairment
Josef Faller1, Reinhold Scherer1, Elisabeth V C Friedrich2
1Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology Graz, Austria.
Frontiers in Neuroscience
|November 5, 2014
Summary
An improved brain-computer interface (BCI) configuration for individuals with severe motor impairment, like spinal cord injury (SCI) or stroke, was identified. The new Auto-AdBCI system significantly enhanced control performance compared to standard motor imagery-based BCIs.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Rehabilitation Technology
Background:
- Event-related desynchronization (ERD) based brain-computer interfaces (BCIs) offer assistive technology for individuals with severe motor impairments.
- Adaptive ERD-based BCIs utilizing motor imagery tasks (SMR-AdBCI) are effective for healthy users but require optimization for clinical populations.
Purpose of the Study:
- To investigate an improved configuration for adaptive ERD-based BCIs tailored for individuals with spinal cord injury (SCI) or stroke.
- To compare the control performance of a novel adaptive BCI (Auto-AdBCI) with a conventional SMR-AdBCI.
Main Methods:
- Offline analysis of electroencephalography (EEG) data from individuals with SCI or stroke across two sessions.
- Identification of optimal bipolar derivations and mental tasks for both SMR-AdBCI and Auto-AdBCI configurations.
- Simulation and comparison of classification performance between the two BCI configurations on unseen data.
Main Results:
- The Auto-AdBCI, which automatically selects user-specific mental task combinations, demonstrated significantly higher classification performance (75.7% accuracy) compared to the SMR-AdBCI (66.3% accuracy) on unseen data (p < 0.01).
- The proposed Auto-AdBCI configuration showed superior efficacy for individuals with SCI or stroke.
Conclusions:
- Automatic selection of user-specific mental task combinations during auto-calibration represents a significant improvement for adaptive ERD-based BCIs in individuals with severe motor impairment.
- The Auto-AdBCI system holds promise for enhancing assistive technology for stroke and SCI survivors.
