An open access database for the evaluation of heart sound algorithms

In the past few decades, analysis of heart sound signals (i.e. the phonocardiogram or PCG), especially for automated heart sound segmentation and classification, has been widely studied and has been reported to have the potential value to detect pathology accurately in clinical applications. However, comparative analyses of algorithms in the literature have been hindered by the lack of high-quality, rigorously validated, and standardized open databases of heart sound recordings. This paper describes a public heart sound database, assembled for an international competition, the PhysioNet/Computing in Cardiology (CinC) Challenge 2016. The archive comprises nine different heart sound databases sourced from…

• AU
  Aalborg Universitet
• DU
  Dalian University of Technology
• IU
  Isfahan University of Medical Sciences
• SU
  Shiraz University
• AU
  Aristotle University of Thessaloniki
• NI
  National Institutes of Health

  Awards: R01-EB001659, R01GM104987
• NI
  National Institute of General Medical Sciences

  Award: R01GM104987
• NI
  National Institute of Biomedical Imaging and Bioengineering

  Award: R01GM104987