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Proceedings Paper

Hyperspectral vital sign signal analysis for medical data
Author(s): Cheng Gao; Yao Li; Hsiao-Chi Li; Chein-I Chang; Peter Hu; Colin Mackenzie
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Paper Abstract

This paper develops a completely new technology,) from a hyperspectral imaging perspective, called Hyperspectral Vital Sign Signal Analysis (HyVSSA. A hyperspectral image is generally acquired by hundreds of contiguous spectral bands, each of which is an optical sensor specified by a particular wavelength. In medical application, we can consider a patient with different vital sign signals as a pixel vector in hyperspectral image and each vital sign signal as a particular band. In light of this interpretation, a revolutionary concept is developed, which translates medical data to hyperspectral data in such a way that hyperspectral technology can be readily applied to medical data analysis. One of most useful techniques in hyperspectral data processing is, Anomaly Detection (AD) which in this medical application is used to predict outcomes such as transfusion, length of stay (LOS) and mortality using various vital signs. This study compared transfusion prediction performance of Anomaly Detection (AD) and Logistic Regression (LR).

Paper Details

Date Published: 21 May 2015
PDF: 7 pages
Proc. SPIE 9501, Satellite Data Compression, Communications, and Processing XI, 950110 (21 May 2015); doi: 10.1117/12.2179608
Show Author Affiliations
Cheng Gao, Univ. of Maryland, Baltimore County (United States)
Yao Li, Univ. of Maryland, Baltimore County (United States)
Hsiao-Chi Li, Univ. of Maryland, Baltimore County (United States)
Chein-I Chang, Univ. of Maryland, Baltimore County (United States)
Peter Hu, Univ. of Maryland School of Medicine (United States)
Colin Mackenzie, Univ. of Maryland School of Medicine (United States)


Published in SPIE Proceedings Vol. 9501:
Satellite Data Compression, Communications, and Processing XI
Bormin Huang; Chein-I Chang; Chulhee Lee; Yunsong Li; Qian Du, Editor(s)

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