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Proceedings Paper

Non-linear algorithms for noise removal from medical signals using the logical transform
Author(s): Ethan E. Danahy; Sos S. Agaian; Karen A. Panetta
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Paper Abstract

During critical situations, the precise digital processing of medical signals such as heartbeats is essential. Outside noise introduced into this data can lead to misinterpretation. Thus, it is important to be able to detect and correct the signal quickly and efficiently using digital filtering algorithms. With filtering, the goal is to remove noise locations by correctly identify the corrupted data points and replacing these locations with acceptable estimations of the original values. However, one has to be careful throughout the filtering process not to also eliminate other important detailed information from the original signal. If the filtered output is to be analyzed post-filtering, say for feature recognition, it is important that both the structure and details of the original clean signal remain. This paper presents an original algorithm and two variations, all using the logical transform, that strive to do this accurately and with low levels of computation. Using real heartbeat signals as test sets, the output is compared to that produced by median type filters, and results demonstrated over a variety of noise levels.

Paper Details

Date Published: 30 August 2005
PDF: 16 pages
Proc. SPIE 5916, Mathematical Methods in Pattern and Image Analysis, 591603 (30 August 2005); doi: 10.1117/12.617153
Show Author Affiliations
Ethan E. Danahy, Tufts Univ. (United States)
Sos S. Agaian, Univ. of Texas/San Antonio (United States)
Karen A. Panetta, Tufts Univ. (United States)


Published in SPIE Proceedings Vol. 5916:
Mathematical Methods in Pattern and Image Analysis
Jaakko T. Astola; Ioan Tabus; Junior Barrera, Editor(s)

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