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ISSN Печать: 0278-940X
ISSN Онлайн: 1943-619X
Indexed in
Advances in Time-Frequency Analysis of Biomedical Signals
Краткое описание
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.
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Guerrero-Mosquera Carlos, Malanda Trigueros Armando, Iriarte Franco Jorge, Navia-Vázquez Ángel, New feature extraction approach for epileptic EEG signal detection using time-frequency distributions, Medical & Biological Engineering & Computing, 48, 4, 2010. Crossref
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Sun Yuge, Ye Ning, Xu Xinhe, EEG Analysis of Alcoholics and Controls Based on Feature Extraction, 2006 8th international Conference on Signal Processing, 2006. Crossref
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Huo Yingda, Li Fubao, Li Qin, He Enqiu, Chen Jichi, Iqbal Nadeem, A Novel Method for Hand Movement Recognition Based on Wavelet Packet Transform and Principal Component Analysis with Surface Electromyogram, Computational Intelligence and Neuroscience, 2022, 2022. Crossref