DocumentCode :
3311233
Title :
Multi-resolution time-frequency analysis for detection of rhythms of EEG signals
Author :
Qin, Shuren ; Ji, Zhong
Author_Institution :
Test Center, Chongqing Univ., China
fYear :
2004
fDate :
1-4 Aug. 2004
Firstpage :
338
Lastpage :
341
Abstract :
In recent years, various time-frequency methods have been applied widely For detecting all kinds of feature waves and abnormal waves in EEG signals. But because of their nature and some inherent limitations, their application in EEG analysis has been limited. Considering the excellence and shortcomings of STFT (short time Fourier transform) and wavelets, in the "virtual EEG recording and analysis instrumentation", the multi-resolution time-frequency analysis method, based on STFT and wavelet packet transform, has been introduced to advance the self-adaptive ability for signals, so more flexible division of frequency bands in EEG can be obtained and the basic rhythms in EEG signals can be detected efficiently.
Keywords :
Fourier transforms; adaptive signal processing; electroencephalography; feature extraction; medical signal processing; time-frequency analysis; virtual instrumentation; wavelet transforms; EEG signal basic rhythm detection; Gabor transform; STFT; abnormal wave detection; feature wave detection; frequency band division; multiresolution time-frequency analysis; self-adaptive analysis ability; short time Fourier transform; virtual EEG recording/analysis instrumentation; wavelet packet transform; Electroencephalography; Fourier transforms; Frequency conversion; Instruments; Rhythm; Signal analysis; Time frequency analysis; Wavelet analysis; Wavelet packets; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing Workshop, 2004 and the 3rd IEEE Signal Processing Education Workshop. 2004 IEEE 11th
Print_ISBN :
0-7803-8434-2
Type :
conf
DOI :
10.1109/DSPWS.2004.1437971
Filename :
1437971
Link To Document :
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