Improved dilation CapsuleNet for motor imagery and mental arithmetic classification based on fNIRS
Yu Li, Tao Xu, Junhua Li, Feng Wan, Hongtao Wang
Abstract
Purpose: This study aimed to improve the accuracy of brain-computer interface (BCI) systems based on motor imagery (MI) and mental arithmetic (MA) by utilizing functional near-infrared spectroscopy (fNIRS) and an improved dilation CapsuleNet (ID-CapsuleNet) model.
Topics & Concepts
Dilation (metric space)Motor imageryMental arithmeticArithmeticPsychologyCognitive psychologyArtificial intelligenceComputer scienceMathematicsElectroencephalographyNeuroscienceBrain–computer interfaceMedicineCombinatoricsRadiologyBlood pressureHeart rateEEG and Brain-Computer InterfacesFace and Expression RecognitionBrain Tumor Detection and Classification