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Computer Science > Information Theory

arXiv:1405.0086 (cs)
[Submitted on 1 May 2014]

Title:Medically Relevant Criteria used in EEG Compression for Improved Post-Compression Seizure Detection

Authors:Hoda Daou, Fabrice Labeau
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Abstract:Biomedical signals aid in the diagnosis of different disorders and abnormalities. When targeting lossy compression of such signals, the medically relevant information that lies within the data should maintain its accuracy and thus its reliability. In fact, signal models that are inspired by the bio-physical properties of the signals at hand allow for a compression that preserves more naturally the clinically significant features of these signals. In this paper, we illustrate this through the example of EEG signals; more specifically, we analyze three specific lossy EEG compression schemes. These schemes are based on signal models that have different degrees of reliance on signal production and physiological characteristics of EEG. The resilience of these schemes is illustrated through the performance of seizure detection post compression.
Comments: This work has been submitted to the IEEE for possible publication
Subjects: Information Theory (cs.IT)
Cite as: arXiv:1405.0086 [cs.IT]
  (or arXiv:1405.0086v1 [cs.IT] for this version)
  https://doi.org/10.48550/arXiv.1405.0086

Submission history

From: Hoda Daou [view email]
[v1] Thu, 1 May 2014 03:53:59 UTC (85 KB)
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