Recently, recording high-resolution Electroencephalograms (EEGs) from a large number of electrodes has become a clear trend in both brain research and clinical diagnosis. However, the current EEG data acquisition systems store the collected data in a form that has never changed since digital EEG emerged about 30 years ago. As a result, the size of the output data file increases enormously as the number of recording channels increases, causing various problems including high costs in data analysis, database management, archiving, and transmission through the internet. This proposal seeks to solve this problem through fundamental research on data compression specifically for EEG data, but applicable to other physiological data as well. Our key approach is based on the application of advanced mathematical and signal processing technologies to this critical problem. We will develop and optimize a variable sampling technique which eliminates redundant data samples using spline interpolation and wavelet transformation. We will also investigate lossless data compression algorithms that possess two important features: 1) any part of the data within the compressed file can be read without having to decompress the entire file, and 2) the compressed data can be transmitted and presented in coarse or fine resolutions as needed. We expect that, using both variable sampling and lossless compression, the EEG file size can be reduced by approximately 70 percent.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS038494-03
Application #
6363936
Study Section
Special Emphasis Panel (ZRG1-IFCN-8 (01))
Program Officer
Heetderks, William J
Project Start
1999-03-01
Project End
2002-02-28
Budget Start
2001-03-01
Budget End
2002-02-28
Support Year
3
Fiscal Year
2001
Total Cost
$177,776
Indirect Cost
Name
University of Pittsburgh
Department
Neurosurgery
Type
Schools of Medicine
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
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Xu, Jian; Sclabassi, Robert J; Liu, Qiang et al. (2007) Human perception based video preprocessing for telesurgery. Conf Proc IEEE Eng Med Biol Soc 2007:3086-9
Jia, Wenyan; Sclabassi, Robert J; Pon, Lin-Sen et al. (2006) Spike separation from EEG/MEG data using morphological filter and wavelet transform. Conf Proc IEEE Eng Med Biol Soc 1:6137-40
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