title: Development and validation of a novel fusion algorithm for continuous, accurate, and automated R-wave detection and calculation of signal-derived metrics.
abstract: OBJECTIVE
  Previous studies have shown that heart rate complexity may be a useful indicator of patient status in the critical care environment but will require continuous, accurate, and automated R-wave detection (RWD) in the electrocardiogram (ECG). Although numerous RWD algorithms exist, accurate detection remains a challenge. The purpose of this study was to develop and validate a novel fusion algorithm (Automated Electrocardiogram Selection of Peaks, or AESOP) that combines the strengths of several well-known algorithms to provide a more reliable real-time solution to the RWD problem.
  
  
  METHODS
  This study involved the ECGs of 108 prehospital patient records and 32 ECGs from a conscious sedated porcine model of hemorrhagic shock. The criterion standard for validation was manual verification of R waves.
  
  
  RESULTS
  For 108 human ECG records, the AESOP algorithm overall outperformed each of its component algorithms. In addition, for 32 swine ECG records, AESOP achieved an R-wave sensitivity of 97.9% and a positive predictive value of 97.5%, again outperforming its component algorithms.
  
  
  CONCLUSIONS
  By fusing several best algorithms, AESOP uses the strengths of each algorithm to perform more robustly and reliably in real time. The AESOP algorithm will be integrated into a real-time heart rate complexity software program for decision support and triage in critically ill patients.
authors.affiliation: US Army Institute of Surgical Research, Fort Sam Houston, TX 78234-6315. Electronic address: nehemiah.liu@us.army.mil.
authors.forename: Nehemiah T
authors.initials: NT
authors.lastname: Liu
authors.forename: Andriy I
authors.initials: AI
authors.lastname: Batchinsky
authors.forename: Leopoldo C
authors.initials: LC
authors.lastname: Cancio
authors.forename: William L
authors.initials: WL
authors.lastname: Baker
authors.forename: Jose
authors.initials: J
authors.lastname: Salinas
mesh_terms: D000465:Algorithms; D000818:Animals; D016638:Critical Illness; D004562:Electrocardiography; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D011237:Predictive Value of Tests; D012771:Shock, Hemorrhagic / Q000503:physiopathology*; D012815:Signal Processing, Computer-Assisted; D013552:Swine
keywords: Automatic data processing; Clinical decision support systems; Electrocardiography; Heart rate complexity; Signal detection analysis