{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T11:14:06Z","timestamp":1788261246489,"version":"build-2803163510"},"reference-count":37,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomimetics"],"abstract":"<jats:p>Traditional P300 brain\u2013computer 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\u2019 psychological and physical burdens (p &lt; 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.<\/jats:p>","DOI":"10.3390\/biomimetics11090613","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T09:48:36Z","timestamp":1788256116000},"page":"613","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Few-Channel Brain\u2013Computer Interface System Based on a Heuristic Algorithm"],"prefix":"10.3390","volume":"11","author":[{"given":"Junhong","family":"Luo","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Guangzhou Maritime University, Guangzhou 510725, China"},{"name":"School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou 510520, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianbin","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Guangzhou Maritime University, Guangzhou 510725, China"},{"name":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Guangzhou Maritime University, Guangzhou 510725, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiyue","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Guangzhou Maritime University, Guangzhou 510725, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinheng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Guangzhou Maritime University, Guangzhou 510725, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Guangzhou Maritime University, Guangzhou 510725, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yuan, J., Zhang, R., Zhao, Y., Zhou, W., Tian, L., and Liu, G. 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