EEG data compression to monitor DoA in telemedicine

Palendeng, Mario E. and Zhang, Qing and Pang, Chaoyi and Li, Yan (2012) EEG data compression to monitor DoA in telemedicine. In: HIC 2012: 20th Australian National Health Informatics Conference: Health Informatics: Building a Healthcare Future Through Trusted Information , 30 Jul-2 Aug 2012, Sydney, Australia.

Abstract

Data compression techniques have been widely used to process and transmit huge amount of EEG data in real-time and remote EEG signal processing systems. In this paper we propose a lossy compression technique, F-shift, to compress EEG signals for remote depth of Anaesthesia (DoA) monitoring. Compared with traditional wavelet compression techniques, our method not only preserves valuable clinical information with high compression ratios, but also reduces high frequency noises in EEG signals. Moreover, our method has negligible compression overheads (less than 0.1 seconds), which can greatly benefit real-time EEG signal monitoring systems. Our extensive experiments demonstrate the efficiency and effectiveness of the proposed compression method.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to published version due to publisher copyright policy. c. 2012 The authors and IOS Press.
Depositing User: Mr Mario Elvis Palendeng
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 25 Oct 2012 05:09
Last Modified: 14 Aug 2014 04:46
Uncontrolled Keywords: EEG data compression; depth of anaesthesia; telemedicine
Fields of Research (FOR2008): 10 Technology > 1005 Communications Technologies > 100504 Data Communications
11 Medical and Health Sciences > 1117 Public Health and Health Services > 111711 Health Information Systems (incl. Surveillance)
08 Information and Computing Sciences > 0804 Data Format > 080403 Data Structures
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: doi: 10.3233/978-1-61499-078-9-163
URI: http://eprints.usq.edu.au/id/eprint/21997

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