title: A frequency-temporal-spatial method for motor-related electroencephalography pattern recognition by comprehensive feature optimization.
abstract: Either imagined or actual movements lead to a combination of electroencephalography signals with distinctive frequency, temporal and spatial characteristics, which correspond to various motor-related neural activities. This frequency-temporal-spatial pattern is the key of motor intention decoding which is the basis of brain-computer interfaces by motor imagery. We present a new method for motor-related electroencephalography recognition which comprehensively optimizes the frequency-time-space features in a user-specific way. The recognition work focuses on three points: proper time and frequency domain segmentation, spatial optimization based on common spatial pattern filters and feature importance evaluation. We show that by combining the advantages of these optimizational methods, the proposed algorithm effectively improves motor task classification, and the recognized signal chanracteristics can be used to visualize the motor related electroencephalography patterns under different conditions.
authors.affiliation: Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China.
authors.forename: Bian
authors.initials: B
authors.lastname: Wu
authors.forename: Fan
authors.initials: F
authors.lastname: Yang
authors.forename: Jicai
authors.initials: J
authors.lastname: Zhang
authors.forename: Yiwen
authors.initials: Y
authors.lastname: Wang
authors.forename: Xiaoxiang
authors.initials: X
authors.lastname: Zheng
authors.forename: Weidong
authors.initials: W
authors.lastname: Chen
mesh_terms: D000328:Adult; D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D016002:Discriminant Analysis; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology; D006801:Humans; D007092:Imagination / Q000502:physiology; D008297:Male; D009048:Motor Skills / Q000502:physiology; D010363:Pattern Recognition, Automated / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface