Decoding Articulation Motor Imagery Using Early Connectivity Information in the Motor Cortex: A Functional Near-Infrared Spectroscopy Study

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 31; pp. 506 - 518
• Main Authors: Guo, Zengzhi, Chen, Fei
• Format: Journal Article
• Language: English
• Published: United States IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Articulation (speech); Brain; Brain computer interface; Classification; command generation time reduction; Computer applications; Cortex (motor); Decoding; Electroencephalography; Feature extraction; Functional near-infrared spectroscopy; Human-computer interface; Implants; Infrared spectra; Infrared spectroscopy; Jaw; Medical imaging; Mental task performance; Movement disorders; Near infrared radiation; Neural networks; Spectrum analysis; Speech; speech imagery; Symbols; Synchronism; Synchronization; synchronization information; Task analysis; Vowels; Windows (intervals)

Brain computer interface (BCI) based on speech imagery can help people with motor disorders communicate their thoughts to the outside world in a natural way. Due to being portable, non-invasive, and safe, functional near-infrared spectroscopy (fNIRS) is preferred for developing BCIs. Previous BCIs b...