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P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
Published on: September 8, 2023
510
A click-based electrocorticographic brain-computer interface enables long-term high-performance switch scan spelling
Daniel N Candrea1, Samyak Shah2, Shiyu Luo3
1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. dcandre3@jh.edu.
Communications Medicine
|October 21, 2024
Summary
Brain-computer interfaces (BCIs) enable communication for impaired individuals. A single command click detector, trained with minimal data, showed robust, long-term performance for text-based communication.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Rehabilitation Technology
Background:
- Brain-computer interfaces (BCIs) offer communication restoration for individuals with severe motor and speech impairments.
- Single command click detectors represent a fundamental yet effective BCI capability.
Purpose of the Study:
- To evaluate the performance and long-term stability of a click decoding system using electrocorticography (ECoG) in a human clinical trial.
- To assess the feasibility of training a BCI click detector with limited data and minimal retraining.
Main Methods:
- A high-density ECoG BCI system was implanted, covering the sensorimotor cortex of a participant with amyotrophic lateral sclerosis.
- The click detector was trained using less than 44 minutes of data across 4 days, up to 21 days before BCI use, and tested for 90 days without retraining.
Main Results:
- The participant achieved a median spelling rate of 10.2 characters per minute using the click detector with a switch scanning speller.
- Despite transient signal power fluctuations, a newly trained click detector demonstrated comparable performance with even less training data (<15 minutes).
Conclusions:
- A click detector can be trained effectively using a small ECoG dataset, maintaining robust performance over extended periods.
- This demonstrates the potential for BCIs with click detectors to provide functional, text-based communication for users.
