High-Frequency Power Reflects Dual Intentions of Time and Movement for Active Brain-Computer Interface DOI Creative Commons
Jiayuan Meng, Xiaoyu Li, Siqi Li

et al.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2025, Volume and Issue: 33, P. 630 - 639

Published: Jan. 1, 2025

Active brain-computer interface (BCI) provides a natural way for direct communications between the brain and devices. However, its detectable intention is very limited, let alone of detecting dual intentions from single electroencephalography (EEG) feature. This study aims to develop time-based active BCI, further investigate feasibility time-movement using EEG A synchronization experiment was designed, which contained both time (500 ms vs. 1000 ms) movement (left right). Behavioural data 22 healthy participants were recorded analyzed in before (BT) after (AT) timing prediction training sessions. Consequently, compared BT sessions, AT sessions led substantially smaller absolute deviation behaviourally, along with larger high-frequency event-related desynchronization (ERD) frontal-motor areas, significantly improved decoding accuracy time. Moreover, achieved enhanced motor-related contralateral dominance potentials (ERP) ERDs than BT, illustrated synergistic relationship two intentions. The feature 20-60 Hz power can simultaneously reflect intentions, achieving 73.27% averaged four-classification ms-left 500 ms-right vs.1000 ms-right), highest up 93.81%. results initiatively verified role (20-60 Hz) representing It not only broadens but also enables it read user's mind concurrently information dimensions.

Language: Английский

High-Frequency Power Reflects Dual Intentions of Time and Movement for Active Brain-Computer Interface DOI Creative Commons
Jiayuan Meng, Xiaoyu Li, Siqi Li

et al.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2025, Volume and Issue: 33, P. 630 - 639

Published: Jan. 1, 2025

Active brain-computer interface (BCI) provides a natural way for direct communications between the brain and devices. However, its detectable intention is very limited, let alone of detecting dual intentions from single electroencephalography (EEG) feature. This study aims to develop time-based active BCI, further investigate feasibility time-movement using EEG A synchronization experiment was designed, which contained both time (500 ms vs. 1000 ms) movement (left right). Behavioural data 22 healthy participants were recorded analyzed in before (BT) after (AT) timing prediction training sessions. Consequently, compared BT sessions, AT sessions led substantially smaller absolute deviation behaviourally, along with larger high-frequency event-related desynchronization (ERD) frontal-motor areas, significantly improved decoding accuracy time. Moreover, achieved enhanced motor-related contralateral dominance potentials (ERP) ERDs than BT, illustrated synergistic relationship two intentions. The feature 20-60 Hz power can simultaneously reflect intentions, achieving 73.27% averaged four-classification ms-left 500 ms-right vs.1000 ms-right), highest up 93.81%. results initiatively verified role (20-60 Hz) representing It not only broadens but also enables it read user's mind concurrently information dimensions.

Language: Английский

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