Concise and scale-specific extraction of biomedically relevant information from visual evoked potential signals: combining factor analysis with wavelet decomposition

Vincent J. Samar; Gauri Kulkarni; Kenneth P. Swartz; Ila Parasnis; Raghuveer M. Rao; Vishwas Udpikar

doi:10.1117/12.188794

11 October 1994 Concise and scale-specific extraction of biomedically relevant information from visual evoked potential signals: combining factor analysis with wavelet decomposition

Vincent J. Samar, Gauri Kulkarni, Kenneth P. Swartz, Ila Parasnis, Raghuveer M. Rao, Vishwas Udpikar

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Proceedings Volume 2303, Wavelet Applications in Signal and Image Processing II; (1994) https://doi.org/10.1117/12.188794
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

The nervous system possesses an intrinsic multiscale organization of processing systems. Evoked potentials (EPs) and other neurometric signals contain corresponding multiscale information about the normal and disordered functioning of the nervous system. The discrete wavelet transform (DWT) explicitly distinguishes among multiple scales of waveform structure, and can be used to decompose EPs in a manner that respects this intrinsic organization. In this paper we provide evidence for the multiscale structure of EPs. We demonstrate that EPs contain scale-specific information of biomedical, neurophysiological, and neuropsychological relevance. Finally, we show that the DWT provides information about small-scale phenomena that is inaccessible by standard neurometric waveform analysis techniques.

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Vincent J. Samar, Gauri Kulkarni, Kenneth P. Swartz, Ila Parasnis, Raghuveer M. Rao, and Vishwas Udpikar "Concise and scale-specific extraction of biomedically relevant information from visual evoked potential signals: combining factor analysis with wavelet decomposition", Proc. SPIE 2303, Wavelet Applications in Signal and Image Processing II, (11 October 1994); https://doi.org/10.1117/12.188794

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