Paper
21 May 2015 Hyperspectral vital sign signal analysis for medical data
Cheng Gao, Yao Li, Hsiao-Chi Li, Chein-I Chang, Peter Hu, Colin Mackenzie
Author Affiliations +
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).
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cheng Gao, Yao Li, Hsiao-Chi Li, Chein-I Chang, Peter Hu, and Colin Mackenzie "Hyperspectral vital sign signal analysis for medical data", Proc. SPIE 9501, Satellite Data Compression, Communications, and Processing XI, 950110 (21 May 2015); https://doi.org/10.1117/12.2179608
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Lawrencium

Data modeling

Vital signs

Signal analysis

Hyperspectral imaging

Blood

Injuries

Back to Top