Developing Hybrid Brain–Computer Interfaces That Integrate fNIRS and EEG Signals for Real-Time Control of Motor Neuroprosthetic Devices
Keywords:
Brain–Computer Interface (BCI), Hybrid BCI, Functional Near-Infrared Spectroscopy (fNIRS), Electroencephalography (EEG), Motor Neuroprosthetics, Real-Time ControlAbstract
Brain–computer interfaces (BCIs) have emerged as a transformative technology for restoring motor function in individuals with neurological impairments. Recent advancements in hybrid BCIs that integrate functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) have demonstrated significant potential in improving the accuracy, speed, and reliability of motor neuroprosthetic control. This paper explores the development of a hybrid BCI system combining fNIRS and EEG signals for real-time motor control, providing a comprehensive review of the literature, technological challenges, and potential applications. Through an analysis of recent studies and data, the paper highlights the synergy between fNIRS and EEG in enhancing BCI performance and suggests future directions for research and development.
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