EEG-Driven Arm Movement Decoding: Combining Connectivity and Amplitude Features for Enhanced Brain–Computer Interface Performance

EEG-Driven Arm Movement Decoding: Combining Connectivity and Amplitude Features for Enhanced Brain–Computer Interface Performance

Brain–computer interfaces (BCIs) translate electroencephalography (EEG) signals into control commands, offering potential solutions for motor-impaired individuals. While traditional BCI studies often focus solely on amplitude variations or inter-channel connectivity, movement-related brain activity...

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Bibliographic Details
Main Authors: Hamidreza Darvishi, Ahmadreza Mohammadi, Mohammad Hossein Maghami, Meysam Sadeghi, Mohamad Sawan
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Bioengineering
Subjects:
brain–computer interface
electroencephalography
electromyography
filter bank common spatial patterns
phase-locking value
neural network
Online Access:https://www.mdpi.com/2306-5354/12/6/614
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