15 October 2012 Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process
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Abstract
Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.
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M. E. Testorf, M. E. Testorf, B. C. Jobst, B. C. Jobst, J. K. Kleen, J. K. Kleen, A. Titiz, A. Titiz, S. Guillory, S. Guillory, R. Scott, R. Scott, K. A. Bujarski, K. A. Bujarski, D. W. Roberts, D. W. Roberts, G. L. Holmes, G. L. Holmes, P.-P. Lenck-Santini, P.-P. Lenck-Santini, } "Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process", Proc. SPIE 8500, Image Reconstruction from Incomplete Data VII, 850008 (15 October 2012); doi: 10.1117/12.930279; https://doi.org/10.1117/12.930279
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