title: Classification of hand movement direction based on EEG high-gamma activity.
abstract: The Electroencephalogram (EEG) is a non-invasive technique used in the medical field to record and analyze brain activity. In particular, Brain Machine Interfaces (BMI) create this bridge between brain signals and the external world through prosthesis, visual interfaces and other physical devices. This paper investigates the relation between particular hand movement directions while using a BMI and the EEG recordings during such movement. The Common Spatial Pattern method (CSP) over the high-γ frequency band is utilized in order to discriminate opposite hand movement directions. The experiment is performed with three subjects and the average classification accuracy is obtained for two different cases.
authors.forename: Carlos A
authors.initials: CA
authors.lastname: Loza
authors.forename: Gavin R
authors.initials: GR
authors.lastname: Philips
authors.forename: Mehrnaz Kh
authors.initials: MKh
authors.lastname: Hazrati
authors.forename: Janis J
authors.initials: JJ
authors.lastname: Daly
authors.forename: Jose C
authors.initials: JC
authors.lastname: Principe
mesh_terms: D062207:Brain-Computer Interfaces; D004569:Electroencephalography; D065818:Gamma Rhythm; D006225:Hand / Q000502:physiology; D006801:Humans; D008297:Male; D009043:Motor Activity; D009044:Motor Cortex / Q000502:physiology; D012815:Signal Processing, Computer-Assisted