DocumentCode :
1613022
Title :
Decomposition of Evoked Potentials using Peak Detection and the Discrete Wavelet Transform
Author :
McCooey, Conor ; Kumar, Dinesh Kant ; Cosic, Irena
Author_Institution :
R. Melbourne Inst. of Technol., Vic.
fYear :
2006
Firstpage :
2071
Lastpage :
2074
Abstract :
A new method of viewing evoked potential data is described. This method, called the peak detection method, is based on singularity detection using the discrete wavelet transform. The peaks and troughs of raw visual evoked potential data are identified and characterized using the algorithms of this method, resulting in a linear decomposition of the recording into sets of individual peaks. The individual peaks are then added together, averaged and compared to the ensemble average signal. The peak detection method correlates strongly to the ensemble average showing that this method retains the same evoked potential signal profile
Keywords :
discrete wavelet transforms; medical signal detection; medical signal processing; visual evoked potentials; discrete wavelet transform; linear decomposition; peak detection; singularity detection; visual evoked potential; Australia; Biomedical engineering; Design methodology; Discrete wavelet transforms; Disk recording; Electroencephalography; Logic arrays; Signal generators; Spline; Wavelet domain; Averaging; Discrete Wavelet Transform; EEG; Singularity Detection; Visual Evoked Potentials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
Type :
conf
DOI :
10.1109/IEMBS.2005.1616866
Filename :
1616866
Link To Document :
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