title: A Signal Processing Approach for Detection of Hemodynamic Instability before Decompensation.
abstract: Advanced hemodynamic monitoring is a critical component of treatment in clinical situations where aggressive yet guided hemodynamic interventions are required in order to stabilize the patient and optimize outcomes. While there are many tools at a physician's disposal to monitor patients in a hospital setting, the reality is that none of these tools allow hi-fidelity assessment or continuous monitoring towards early detection of hemodynamic instability. We present an advanced automated analytical system which would act as a continuous monitoring and early warning mechanism that can indicate pending decompensation before traditional metrics can identify any clinical abnormality. This system computes novel features or bio-markers from both heart rate variability (HRV) as well as the morphology of the electrocardiogram (ECG). To compare their effectiveness, these features are compared with the standard HRV based bio-markers which are commonly used for hemodynamic assessment. This study utilized a unique database containing ECG waveforms from healthy volunteer subjects who underwent simulated hypovolemia under controlled experimental settings. A support vector machine was utilized to develop a model which predicts the stability or instability of the subjects. Results showed that the proposed novel set of features outperforms the traditional HRV features in predicting hemodynamic instability.
authors.affiliation: Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.|Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, Michigan, United States of America.
authors.forename: Ashwin
authors.initials: A
authors.lastname: Belle
authors.affiliation: Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.|Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, Michigan, United States of America.
authors.forename: Sardar
authors.initials: S
authors.lastname: Ansari
authors.affiliation: College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, Michigan, United States of America.
authors.forename: Maxwell
authors.initials: M
authors.lastname: Spadafore
authors.affiliation: Combat Casualty Care Research Program US Army Institute of Surgical Research, San Antonio, Texas, United States of America.
authors.forename: Victor A
authors.initials: VA
authors.lastname: Convertino
authors.affiliation: Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.|Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, Michigan, United States of America.
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Ward
authors.affiliation: Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Mathematics, University of Michigan, Ann Arbor, Michigan, United States of America.
authors.forename: Harm
authors.initials: H
authors.lastname: Derksen
authors.affiliation: Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.|Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bio-informatics, University of Michigan, Ann Arbor, Michigan, United States of America.
authors.forename: Kayvan
authors.initials: K
authors.lastname: Najarian
mesh_terms: D015415:Biomarkers / Q000032:analysis; D001794:Blood Pressure; D042241:Early Diagnosis; D004562:Electrocardiography / Q000706:statistics & numerical data; D064368:Healthy Volunteers; D006333:Heart Failure / Q000175:diagnosis* / Q000503:physiopathology; D006339:Heart Rate; D006439:Hemodynamics; D006801:Humans; D020896:Hypovolemia / Q000175:diagnosis* / Q000503:physiopathology; D008991:Monitoring, Physiologic / Q000295:instrumentation / Q000379:methods*; D066230:Patient-Specific Modeling / Q000706:statistics & numerical data*; D060388:Support Vector Machine
chemical_list: D015415:Biomarkers