title: Advances in time-frequency analysis of biomedical signals.
abstract: The frequency content of many biomedical signals can change rapidly with time. Conventional Fourier spectral analysis techniques are insufficient for analyzing the time-varying spectral content of these signals. By mapping a one-dimensional function of time (or frequency), the time-frequency representation can localize the signal energy in both the time and frequency directions. It has been shown that many biomedical signal problems may benefit from time-frequency analysis. The objective of this paper is to review the advances in time-frequency analysis of biomedical signals. Relevant theoretical methodologies and practical considerations are introduced, and five application areas are reviewed: electroencephalography (EEG), electrocardiography, phonocardiography, electrogastrography, and electromyography.
authors.affiliation: Department of Medicine, University of Kansas Medical Center, Kansas City 66160-7350, USA.
authors.forename: Z
authors.initials: Z
authors.lastname: Lin
authors.forename: J D
authors.initials: JD
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D000818:Animals; D004562:Electrocardiography; D004569:Electroencephalography; D004576:Electromyography; D004594:Electrophysiology / Q000379:methods*; D004833:Epilepsy, Temporal Lobe / Q000175:diagnosis; D005071:Evoked Potentials; D005260:Female; D005583:Fourier Analysis; D006347:Heart Sounds; D006350:Heart Valve Prosthesis; D006801:Humans; D008297:Male; D015233:Models, Statistical; D010701:Phonocardiography; D012016:Reference Values; D012135:Respiratory Sounds; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors