title: A detection scheme for frontalis and temporalis muscle EMG contamination of EEG data.
abstract: Electroencephalogram (EEG) recordings are highly susceptible to noise from electromyogram (EMG) signals of the frontalis and temporalis muscles. In this paper, we propose and evaluate a new method for detecting frontalis and temporalis muscle EMG contamination in EEG signals based on recent findings on topographic and spectral characteristics of cranial EMG.
authors.affiliation: Dept. of Electr. Eng. & Comput. Sci., Case Western Reserve Univ., Cleveland, OH 44106, USA. mjfu@case.edu
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Fu
authors.forename: Janis J
authors.initials: JJ
authors.lastname: Daly
authors.forename: M Cenk
authors.initials: MC
authors.lastname: Cavuşoğlu
mesh_terms: D000328:Adult; D000465:Algorithms; D001931:Brain Mapping / Q000379:methods; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D004576:Electromyography / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D005152:Facial Muscles / Q000033:anatomy & histology*; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009119:Muscle Contraction; D018482:Muscle, Skeletal; D012815:Signal Processing, Computer-Assisted; D013703:Temporal Muscle / Q000033:anatomy & histology*; D014584:User-Computer Interface