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. 2025 Aug 12;19:1625279. doi: 10.3389/fninf.2025.1625279

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Copyright © 2025 Tarara, Przybył, Schöning and Gunia.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Flowchart of a process beginning with a generic stream reader, passing through a bandpass filter and a CSP spatial filter. It branches into five paths labeled Left Hand, Right Hand, Torso Left, Torso Right, and Tongue. Each path undergoes stimulation-based and time-based epoching, signal power logging, and feature aggregation. All paths converge at an SVM classifier trainer, ultimately connecting to a player controller. Arrows indicate the sequence of operations. — Screenshots of OpenViBE support vector classification (SVC) Trainer algorithm. Combination of pipeline steps for training the SVC algorithm consisting of following steps: Bandpass filter 8–13 Hz Box, common spatial pattern (CSP) spatial filter box, Stimulation based epoching boxes (Left Hand, Right Hand, Torso Left, Torso Right, Tongue), Time based epoching box, Signal Power Log box, Feature aggregator box and SVM classifier trainer box.