Technology Developments & Applications for Human-Robot Interaction/Brain-Computer Interface, Surgical Monitoring/Imaging, Rehabilitation, etc.
Brain-computer interface (BCI) technology, which converts brain activity into device commands, is revolutionizing fields such as motor rehabilitation, assistive technology, and virtual reality. It employs methods like functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) to measure brain function—fNIRS tracks changes in blood oxygenation, while EEG detects electrical activity. Both are favored in BCIs for their non-invasiveness, affordability, and adaptability for long-term use. Nevertheless, they have distinct trade-offs: EEG boasts high temporal resolution but suffers from low spatial resolution and motion sensitivity; fNIRS provides better spatial specificity and is less affected by user movement but is limited by slower hemodynamic responses.
The integration of fNIRS and EEG into a multi-modal BCI harnesses the advantages of each: EEG's temporal precision combined with fNIRS's spatial accuracy provides a more robust measurement and decoding of brain activity. This multimodal approach can improve command classification accuracy and enrich our understanding of the coupling between neuronal activity and blood flow, offering significant benefits in neurorehabilitation for patients with motor impairments.
Our goal is to develop an advanced, fully wearable multimodal BCI system that incorporates various measurement techniques including optical imaging, electrophysiology, and bio-impedance. This system aims to merge the unique benefits of each method, providing comprehensive and concurrent information to enhance the performance and application range of BCIs and human-robot interactions (HRI). By achieving higher spatial-temporal resolution and greater user comfort, this new technology aspires to be the gold standard for BCIs, pushing the boundaries of HRI and facilitating more natural and effective human-machine collaboration.
By reaching enhanced spatial-temporal resolution and improved user comfort, this emerging technology aims to advancing the scope of BCI and human-robot interaction (HRI), facilitating more natural and effective human-machine collaboration.