A novel heart-mobile interface for detection and classification of heart sounds

Shanti R. Thiyagaraja, Ram Dantu, Pradhumna L. Shrestha, Anurag Chitnis, Mark A. Thompson, Pruthvi T. Anumandla, Tom Sarma, Siva Dantu

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


Diagnosis of heart disease requires that a medical practitioner investigate heart auscultations for irregular sounds, followed by echocardiography and electrocardiography tests. These expensive tests also require specialized technicians to operate. We present a low-cost, patient-centered device for the initial screening of the heart sounds that can be potentially used by the users on themselves. They can later share these readings with their healthcare providers. We have created an innovative mobile-health service platform for analyzing and classifying heart sounds. The presented system enables remote patient-monitoring by integrating advanced wireless communications with a customized low-cost stethoscope. This system also permits remote management of a patient's cardiac status while maximizing patient mobility. The smartphone application facilitates recording, processing, visualizing, listening to, and classification of heart sounds. We build our classification model using the Mel-Frequency Cepstral Coefficient and Hidden Markov Model. This application is tested in a hospital environment to collect live recordings from patients with positive results. The smartphone application correctly detected 92.68% of abnormal heart conditions in clinical trials at UT Southwestern Hospital.

Original languageEnglish (US)
Pages (from-to)313-324
Number of pages12
JournalBiomedical Signal Processing and Control
StatePublished - Aug 2018


  • Heart sound classification
  • Hidden Markov Model
  • Mel-Frequency Cepstral Coefficient
  • Signal processing
  • Smartphone application
  • Split detection

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Health Informatics


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