Share Email Print
cover

Proceedings Paper

Hyperspectral analysis approach to prioritizing vital sign signals for medical data
Author(s): Li-Chien Lee; Cheng Gao; Chien-Yu Lin; Chein-I Chang; Peter Hu; Colin Mackenzie
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

When medical data are collected there are many Vital Sign Signals (VSSs) that can be used for data analysis. From a hyperspectral imaging perspective, 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 this paper develops two new concepts of prioritization of VSSs. One is Orthogonal Subspace Projection Residual (OSPR), which measures the residual of a VSS in the orthogonal complement subspace to the space linearly spanned by the remaining VSSs. Another is to construct a histogram for each of VSSs that can be used as a means of ranking VSSs according to a certain criterion for optimality. Several measures are proposed to be used as criteria for VSS prioritization, which are variance, entropy and Kullbak-Leibler (KL) information measure. VSS prioritization can then be used as the VSS selection method to form Logistic Regression model (LRM). In order to determine how many VSSs should be used a recently developed concept, called Virtual Dimensionality (VD) can be used for this purpose. To demonstrate the utility of VSS prioritization, data collected in University of Maryland, School of Medicine, Shock Trauma Center (STC) was used for experiments.

Paper Details

Date Published: 19 May 2016
PDF: 9 pages
Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740L (19 May 2016); doi: 10.1117/12.2223918
Show Author Affiliations
Li-Chien Lee, Univ. of Maryland, Baltimore County (United States)
Cheng Gao, Univ. of Maryland, Baltimore County (United States)
Chien-Yu Lin, 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. 9874:
Remotely Sensed Data Compression, Communications, and Processing XII
Bormin Huang; Chein-I Chang; Chulhee Lee, Editor(s)

© SPIE. Terms of Use
Back to Top