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Proceedings Paper

Estimation of confidence levels for physiology variables measured by a vital signs detection system
Author(s): Jingyu Liu; Thomas M. McKenna; Andrei Gribok; Beth A. Beidleman; William T. Tharion; Jaques Reifman
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Paper Abstract

Quantifying the accuracy of physiological data measured by a Vital Signs Detection System (VSDS) plays a key role in making trustworthy decisions about the physiological status of a soldier. We developed an algorithm to report VSDSmeasured heart and respiratory rates and their associated confidence levels. Heart and respiratory rates were measured about every 2 seconds for about 4 hours, while subjects engaged in low (e.g., sitting), medium (e.g., sit-ups), and high intensity (e.g., running) activities. The mean heart and median respiratory rates are calculated every 15 seconds by an in-house developed algorithm, and associated confidence levels for each variable are estimated simultaneously using a fuzzy-logic-based algorithm. Inputs into the algorithm are features that represent two types of information; the quality of each variable, and the relationship between the variables. Faulty data points are separated from good measures by setting a threshold. When data with pre-classified faults are tested with the confidence level threshold set at 0.5, the sensitivity and specificity of the algorithm for heart rate are 91% and 97%, respectively. For respiratory rate, because of the intrinsically noisy property of the data, the sensitivity and specificity are 87% and 93%, respectively. These preliminary results demonstrate that the fuzzy logic algorithm can accurately qualify heart and respiratory rates measured by a VSDS.

Paper Details

Date Published: 19 May 2006
PDF: 8 pages
Proc. SPIE 6218, Chemical and Biological Sensing VII, 621818 (19 May 2006); doi: 10.1117/12.665965
Show Author Affiliations
Jingyu Liu, U.S. Army Medical Research and Material Command (United States)
Thomas M. McKenna, U.S. Army Medical Research and Material Command (United States)
Andrei Gribok, U.S. Army Medical Research and Material Command (United States)
Beth A. Beidleman, U.S. Army Research Institute of Environmental Medicine (United States)
William T. Tharion, U.S. Army Research Institute of Environmental Medicine (United States)
Jaques Reifman, U.S. Army Medical Research and Material Command (United States)


Published in SPIE Proceedings Vol. 6218:
Chemical and Biological Sensing VII
Patrick J. Gardner; Augustus W. Fountain, Editor(s)

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