Departmental Papers (CIS)

Date of this Version

4-13-2015

Document Type

Conference Paper

Comments

6th Workshop on Medical Cyber-Physical Systems (MedicalCPS 2015) http://workshop.medcps.org/ in conjunction with CPS Week 2015 http://www.cpsweek.org/2015/ Seattle, WA, April 13, 2015

An extended version of this paper is available at http://repository.upenn.edu/cis_papers/787/

Abstract

Hypovolemia caused by internal hemorrhage is a major cause of death in critical care patients. However, hypovolemia is difficult to diagnose in a timely fashion, as obvious symptoms do not manifest until patients are already nearing a critical state of shock. Novel non-invasive methods for detecting hypovolemia in the literature utilize the photoplethysmogram (PPG) waveform generated by the pulse-oximeter attached to a finger or ear. Until now, PPG-based alarms have been evaluated only on healthy patients under ideal testing scenarios (e.g., motionless patients); however, the PPG is sensitive to patient health and significant artifacts manifest when patients move. Since patient health varies within the intensive care unit (ICU) and ICU patients typically do not remain motionless, this work introduces a PPG-based monitor designed to be robust to waveform artifacts and health variability in the underlying patient population. To demonstrate the promise of our approach, we evaluate the proposed monitor on a small sample of intensive care patients from the Physionet database. The monitor detects hypovolemia within a twelve hour window of nurse documentation of hypovolemia when it is present, and achieves a low false alarm rate over patients without documented hypovolemia.

Subject Area

CPS Medical

Publication Source

6th Workshop on Medical Cyber-Physical Systems (MedicalCPS 2015)

Keywords

Time series analysis, Medical Information Systems

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Date Posted: 04 May 2015

This document has been peer reviewed.