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Proceedings Paper

Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process
Author(s): M. E. Testorf; B. C. Jobst; J. K. Kleen; A. Titiz; S. Guillory; R. Scott; K. A. Bujarski; D. W. Roberts; G. L. Holmes; P.-P. Lenck-Santini
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Paper 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.

Paper Details

Date Published: 15 October 2012
PDF: 10 pages
Proc. SPIE 8500, Image Reconstruction from Incomplete Data VII, 850008 (15 October 2012); doi: 10.1117/12.930279
Show Author Affiliations
M. E. Testorf, Dartmouth College (United States)
B. C. Jobst, Dartmouth College (United States)
J. K. Kleen, Dartmouth College (United States)
A. Titiz, Dartmouth College (United States)
S. Guillory, Dartmouth College (United States)
R. Scott, Dartmouth College (United States)
K. A. Bujarski, Dartmouth College (United States)
D. W. Roberts, Dartmouth College (United States)
G. L. Holmes, Dartmouth College (United States)
P.-P. Lenck-Santini, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 8500:
Image Reconstruction from Incomplete Data VII
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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