NDLI: EEG compression using JPEG2000: How much loss is too much?

Content Provider	IEEE Xplore Digital Library
Author	Higgins, G. Faul, S. McEvoy, R.P. McGinley, B. Glavin, M. Marnane, W.P. Jones, E.
Copyright Year	2010
Description	Author affiliation: College of Engineering and Informatics, National University of Ireland Galway, University Road, Ireland (Higgins, G.; McGinley, B.; Glavin, M.; Jones, E.) \|\| Department of Electrical & Electronic Engineering, University College Cork, Western Road, Ireland (Faul, S.; McEvoy, R.P.; Marnane, W.P.)
Abstract	Compression of biosignals is an important means of conserving power in wireless body area networks and ambulatory monitoring systems. In contrast to lossless compression techniques, lossy compression algorithms can achieve higher compression ratios and hence, higher power savings, at the expense of some degradation of the reconstructed signal. In this paper, a variant of the lossy JPEG2000 algorithm is applied to Electroencephalogram (EEG) data from the Freiburg epilepsy database. By varying compression parameters, a range of reconstructions of varying signal fidelity is produced. Although lossy compression has been applied to EEG data in previous studies, it is unclear what level of signal degradation, if any, would be acceptable to a clinician before diagnostically significant information is lost. In this paper, the reconstructed EEG signals are applied to REACT, a state-of-the-art seizure detection algorithm, in order to determine the effect of lossy compression on its seizure detection ability. By using REACT in place of a clinician, many hundreds of hours of reconstructed EEG data are efficiently analysed, thereby allowing an analysis of the amount of EEG signal distortion that can be tolerated. The corresponding compression ratios that can be achieved are also presented.
Starting Page	614
Ending Page	617
File Size	389358
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5628020
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Transform coding Image coding Databases Compression algorithms Epilepsy Wireless communication
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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