title: Detection of premature ventricular contractions using the RR-interval signal: a simple algorithm for mobile devices.
abstract: BACKGROUND
  Premature ventricular contractions (PVCs) are cardiac abnormalities that may occur in subjects with/without cardiovascular disorder. Detection is usually performed from electrocardiograms (ECGs); heart activity for a long period of time must be recorded at hospital or with ambulatory electrocardiography. An alternative with a common mobile device would be very interesting, because a simple heart rate sensor should be sufficient.
  
  
  OBJECTIVE
  To develop an algorithm to detect PVCs using the RR-interval (distance between consecutive beats) extracted from ECGs or from the heart rate signal captured by mobile devices.
  
  
  METHODS
  Feature extraction and classification techniques were included: 1) two timing interval features (prematurity and compensatory pause) were extracted. 2) A linear classifier was applied. To validate the method, the MIT-BIH Arrhythmia Database was used. Considering the existence of unbalanced classes (normal beats and PVCs) at different decision costs, validation was performed with receiver operating characteristic (ROC) analysis.
  
  
  RESULTS
  A sensitivity of 90.13% and a specificity percentage of 82.52% were achieved. The area under the ROC curve (AUC) was 0.928.
  
  
  CONCLUSIONS
  The method is advantageous since it only uses the RR-interval signal for PVC detection, and results compare well with more complex methods that use ECG recording.
authors.affiliation: Department of Computer Science, ESEI, University of Vigo, Ourense, Spain.
authors.forename: Pedro
authors.initials: P
authors.lastname: Cuesta
authors.affiliation: Department of Computer Science, ESEI, University of Vigo, Ourense, Spain.
authors.forename: María J
authors.initials: MJ
authors.lastname: Lado
authors.affiliation: Department of Computer Science, ESEI, University of Vigo, Ourense, Spain.
authors.forename: Xosé A
authors.initials: XA
authors.lastname: Vila
authors.affiliation: Department of Computer Science, ESEI, University of Vigo, Ourense, Spain.
authors.forename: Raúl
authors.initials: R
authors.lastname: Alonso
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D015716:Electrocardiography, Ambulatory / Q000295:instrumentation* / Q000379:methods; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D063731:Mobile Applications; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D012815:Signal Processing, Computer-Assisted; D018879:Ventricular Premature Complexes / Q000175:diagnosis*
keywords: ECG; Heart rate; biomedical signal processing; linear classifiers; pattern recognition; premature ventricular contractions