title: A piecewise geometric analysis method for real-time ambulatory ECG detection.
abstract: BACKGROUND
  As one of the pervasive healthcare services, Ubiquitous cardiac care (UCC) systems should have at least two significant characteristics: real-time detection capability for cardiac arrhythmia events and a small resource requirement for its computation and storage.
  
  
  OBJECTIVE
  Due to the strict-constrained system support and ambulatory signal quality in the out-of-hospital pervasive healthcare applications, a dedicated real-time AED (Ambulatory Electrocardiograph Detection) algorithm has been implemented.
  
  
  METHODS
  By adopting the piecewise geometric analysis method, this algorithm can provide a real-time continuous detection capability for QRS complexes, which consists of three main functional modules: the Data preparation; the R-wave vertex discovery; and the QRS complex recognition. Currently, this algorithm has been applied on an on-line UCC application system at the hospital for more than 30 patients.
  
  
  RESULTS
  The performance evaluation has been made not only on the standard MIT-BIH cardiac arrhythmia database but also on the clinical testing. The experiential results explore this algorithm has in average sensitivity of 99.37% and specificity of 99.72%.
  
  
  CONCLUSIONS
  This AED algorithm has minimal beat detection latency and a less computation consumption, which make it meet the requirements of ubiquitous cardiac care applications.
authors.affiliation: School of Electrical and Information Engineering, HuBei University of Automotive Technology, Shiyan, HuBei, China.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China.
authors.forename: H-Y
authors.initials: HY
authors.lastname: Zhou
authors.affiliation: School of Electrical and Information Engineering, HuBei University of Automotive Technology, Shiyan, HuBei, China.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China.
authors.forename: J
authors.initials: J
authors.lastname: Li
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China.
authors.forename: D-C
authors.initials: DC
authors.lastname: Zuo
authors.affiliation: LIMOS Laboratory CNRS UMR, University of Blaise Pascal, Clermont-Ferrand, France.
authors.forename: K-M
authors.initials: KM
authors.lastname: Hou
authors.affiliation: LIMOS Laboratory CNRS UMR, University of Blaise Pascal, Clermont-Ferrand, France.
authors.forename: C de
authors.initials: Cd
authors.lastname: Vaulx
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D006801:Humans; D058998:Remote Sensing Technology / Q000379:methods*; D012815:Signal Processing, Computer-Assisted
keywords: QRS complex detection; Ubiquitous cardiac care; ambulatory ECG; piecewise geometric analysis