Comparison of spike sorting and thresholding of voltage waveforms for intracortical brain-machine interface performance

Journal of Neural Engineering

Volumn 12, Issue 1, 2015, Pages

  Christie, Breanne P ^a   Tat, Derek M ^a   Irwin, Zachary T ^a   Gilja, Vikash ^b,c,d   Nuyujukian, Paul ^b,e   Foster, Justin D ^b   Ryu, Stephen I ^b,f   Shenoy, Krishna V ^b,g   Thompson, David E ^a,h   Chestek, Cynthia A ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

^b Stanford University   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^f PALO ALTO MEDICAL FOUNDATION   (United States)

^g STANFORD UNIVERSITY   (United States)

^h Kansas State University   (United States)

Author keywords

Brain machine interface; Keywords; Spike sorting; Threshold

Indexed keywords

ANIMALS; DECODING; ELECTROPHYSIOLOGY; NEURONS; SODIUM;

BRAIN MACHINE INTERFACE; BRAIN MACHINE INTERFACE (BMIS); CORRELATION COEFFICIENT; KEYWORDS; MIXTURE OF GAUSSIANS; PROSTHETICS APPLICATION; SPIKE-SORTING; THRESHOLD;

SORTING;

ACTION POTENTIAL; ANIMAL EXPERIMENT; ARTICLE; BAYESIAN LEARNING; BRAIN COMPUTER INTERFACE; ELECTRIC POTENTIAL; HAND MOVEMENT; INTERMETHOD COMPARISON; INTRACORTICAL BRAIN MACHINE INTERFACE; MICROELECTRODE; NONHUMAN; PRIORITY JOURNAL; RHESUS MONKEY; SIGNAL PROCESSING; SINGLE UNIT ACTIVITY; SPIKE SORTING; SPIKE WAVE; VOLTAGE WAVEFORM THRESHOLDING; WAVEFORM; ALGORITHM; ANIMAL; AUTOMATED PATTERN RECOGNITION; BRAIN MAPPING; COMPARATIVE STUDY; EVALUATION STUDY; MOTOR CORTEX; NERVE CELL; NERVE CELL NETWORK; PHYSIOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS;

ANIMALIA; MACACA MULATTA;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; BRAIN MAPPING; BRAIN-COMPUTER INTERFACES; DATA INTERPRETATION, STATISTICAL; MACACA MULATTA; MOTOR CORTEX; NERVE NET; NEURONS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84921869507     PISSN: 17412560     EISSN: 17412552     Source Type: Journal    
DOI: 10.1088/1741-2560/12/1/016009     Document Type: Article

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