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arXiv AI By Dekka Muni Kumar, Yogesh Kumar Meena

A Multi-Objective Optimisation Framework for Corticomuscular EEG-EMG Pair Selection in Hybrid BCI

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The paper presents a data‑driven framework that selects optimal EEG‑EMG channel pairs for hybrid brain‑computer interfaces by formulating the problem as a constrained bi‑objective optimisation. It maximises both the spatial relevance of EEG channels to motor cortex areas and the corticomuscular coupling strength, solved with NSGA‑II. Applied to motor‑imagery data from eight stroke patients, the method achieved an average classification accuracy of 89.6%, indicating improved capture of physiologically meaningful interactions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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