A fuzzy logic model for hand posture control using human cortical activity recorded by micro-ECog electrodes

作者: R. Vinjamuri , D.J. Weber , A.D. Degenhart , J.L. Collinger , G.P. Sudre

DOI: 10.1109/IEMBS.2009.5332746

关键词: Wired gloveComputer visionPower (physics)Cerebral cortexArtificial intelligenceComputer scienceMotor cortexAccelerationElectroencephalographyElectrode arrayFuzzy logicSimulationNeurophysiology

摘要: This paper presents a fuzzy logic model to decode the hand posture from electro-cortico graphic (ECoG) activity of motor cortical areas. One subject was implanted with micro-ECoG electrode array on surface cortex. Neural signals were recorded 14 electrodes this while Subject participated in three reach and grasp sessions. In each session, reached grasped wooden toy hammer for five times. Optimal channels/electrodes which active during task selected. Power spectral densities optimal channels averaged over time period 1/2 second before onset movement 1 after fed into model. decoded whether is open or closed 80% accuracy. Hand postures along by using output two methods (i) velocity based decoding (ii) acceleration decoding. The latter performed better when predicted compared data glove experiment. imported MATLAB®SIMULINK control virtual hand.

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