Hyperspectral analysis approach to prioritizing vital sign signals for medical data

Li-Chien Lee; Cheng Gao; Chien-Yu Lin; Chein-I Chang; Peter Hu; Colin Mackenzie

doi:10.1117/12.2223918

19 May 2016 Hyperspectral analysis approach to prioritizing vital sign signals for medical data

Li-Chien Lee, Cheng Gao, Chien-Yu Lin, Chein-I Chang, Peter Hu, Colin Mackenzie

Proceedings Volume 9874, Remotely Sensed Data Compression, Communications, and Processing XII; 98740L (2016) https://doi.org/10.1117/12.2223918
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

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.

Citation Download Citation

Li-Chien Lee, Cheng Gao, Chien-Yu Lin, Chein-I Chang, Peter Hu, and Colin Mackenzie "Hyperspectral analysis approach to prioritizing vital sign signals for medical data", Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740L (19 May 2016); https://doi.org/10.1117/12.2223918

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