Mental State Estimation for Brain--Computer Interfaces
Copyright policy )Mental State Estimation for Brain--Computer Interfaces
Mental state estimation is potentially useful for the development of asynchronous brain--computer interfaces. In this study, four mental states have been identified and decoded from the electrocorticograms (ECoGs) of six epileptic patients, engaged in a memory reach task. A novel signal analysis technique has been applied to high-dimensional, statistically sparse ECoGs recorded by a large number of electrodes. The strength of the proposed technique lies in its ability to jointly extract spatial and temporal patterns, responsible for encoding mental state differences. As such, the technique offers a systematic way of analyzing the spatiotemporal aspects of brain information processing and may be applicable to a wide range of spatiotemporal neurophysiological signals.
- University of California, Santa Barbara United States
- California Institute of Technology United States
- University of California, Irvine United States
570, electrocorticograms (ECoGs), brain, Movement, curse of dimensionality, small sample size problem. Controlled Indexing: bioelectric phenomena, statistically sparse ECoG recording., Pattern Recognition, Automated, brain-computer interfaces, User-Computer Interface, statistically sparse ECoG recording, spatiotemporal neurophysiological signal, Humans, spatiotemporal phenomena, signal temporal pattern extraction, medical signal processing, brain information processing, Epilepsy, feature extraction, biomedical electronics, Brain--computer interfaces (BCIs), Brain, Electroencephalography, Signal Processing, Computer-Assisted, epileptic patient neurophysiological memory reach task, signal analysis technique, 004, classification, biomedical electrodes, Mental Recall, Arm, decoding feature extraction, patient diagnosis, electrocorticogram electrode decoding, neurophysiology, brain mental state estimation, mental states, Algorithms, medical disorders, statistical analysis. Non-controlled Indexing: asynchronous brain-computer interface
570, electrocorticograms (ECoGs), brain, Movement, curse of dimensionality, small sample size problem. Controlled Indexing: bioelectric phenomena, statistically sparse ECoG recording., Pattern Recognition, Automated, brain-computer interfaces, User-Computer Interface, statistically sparse ECoG recording, spatiotemporal neurophysiological signal, Humans, spatiotemporal phenomena, signal temporal pattern extraction, medical signal processing, brain information processing, Epilepsy, feature extraction, biomedical electronics, Brain--computer interfaces (BCIs), Brain, Electroencephalography, Signal Processing, Computer-Assisted, epileptic patient neurophysiological memory reach task, signal analysis technique, 004, classification, biomedical electrodes, Mental Recall, Arm, decoding feature extraction, patient diagnosis, electrocorticogram electrode decoding, neurophysiology, brain mental state estimation, mental states, Algorithms, medical disorders, statistical analysis. Non-controlled Indexing: asynchronous brain-computer interface
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