# A Few-Channel Brain-Computer Interface System Based on a Heuristic Algorithm

Article · Luo J, Yu J, Cao H, Tan Q, Chen J, Xiao J

- Archive id: doi:10.3390/biomimetics11090613
- Published: 2026-09-01
- Venue: Biomimetics (Basel, Switzerland)
- DOI: https://doi.org/10.3390/biomimetics11090613
- PMID: 42782640
- PMCID: PMC13604601
- Citations: 0
- Source URL: https://doi.org/10.3390/biomimetics11090613
- PDF: https://europepmc.org/articles/PMC13604601/pdf
- Provenance: europepmc

## Abstract

Traditional P300 brain-computer interface (BCI) systems rely on multi-channel EEG acquisition, causing cumbersome setup, lengthy preparation, and high user workloads, which limits their real-world application. To enhance practicality, this paper proposes a fixed few-channel selection framework based on a heuristic algorithm to balance decoding performance and user experience. We integrated a genetic algorithm (GA) with Bayesian linear discriminant analysis (BLDA) to identify a strongly generalizable few-channel combination from a traditional eight-channel system, avoiding costly subject-specific recalibration. Validating this method, 48 healthy subjects completed rigorous offline and online virtual reality (VR) experiments. Results showed that the proposed three-channel system maintained highly comparable accuracy and information transfer rates to the eight-channel system, showing no significant performance degradation. Crucially, the few-channel scheme reduced equipment preparation time by 90% (from 30 to 3 min). Furthermore, NASA-TLX workload evaluations confirmed a significant reduction in users' psychological and physical burdens ( p \< 0.05). Ultimately, while preserving core interaction performance, this few-channel strategy vastly improves user experience and system practicality, offering key theoretical and practical support for implementing lightweight, user-friendly BCI systems.

_Abstract reproduced under CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)._

Topics: [Brain-Computer Interfaces](https://space-kitty.com/topics/brain-computer-interfaces)

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