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Voice reduction in cardiac auscultation sounds with reference signals measured from vocal resonators.

Soyun HwangHee Su LeeChan Hun ParkJae Yun JungJung Chan Lee
Published in: The Journal of the Acoustical Society of America (2024)
This study proposes the use of vocal resonators to enhance cardiac auscultation signals and evaluates their performance for voice-noise suppression. Data were collected using two electronic stethoscopes while each study subject was talking. One collected auscultation signal from the chest while the other collected voice signals from one of the three voice resonators (cheek, back of the neck, and shoulder). The spectral subtraction method was applied to the signals. Both objective and subjective metrics were used to evaluate the quality of enhanced signals and to investigate the most effective vocal resonator for noise suppression. Our preliminary findings showed a significant improvement after enhancement and demonstrated the efficacy of vocal resonators. A listening survey was conducted with thirteen physicians to evaluate the quality of enhanced signals, and they have received significantly better scores regarding the sound quality than their original signals. The shoulder resonator group demonstrated significantly better sound quality than the cheek group when reducing voice sound in cardiac auscultation signals. The suggested method has the potential to be used for the development of an electronic stethoscope with a robust noise removal function. Significant clinical benefits are expected from the expedited preliminary diagnostic procedure.
Keyphrases
  • air pollution
  • primary care
  • left ventricular
  • magnetic resonance
  • cross sectional
  • deep learning
  • big data
  • machine learning
  • atrial fibrillation