A pragmatic study on patient friendly treatment: Implementing Dhoulath’s method for separation of cardiac signals from speech for cases including COVID-19 patients

Abstract

The world is barely sighing relief from the Covid-19 pandemic. The auscultation of patients in trauma is very challenging especially in noisy environments. This situation demands a technology that will allow doctors to diagnose accurately regardless of any interference. The proposed method offers a completely non-invasive and patient-friendly procedure that doctors can easily utilize while diagnosing patients. This paper focuses on the separation of aortic regurgitation heart sounds from speech. Here the mixture is an artificial delayed blend of a speech and aortic regurgitation murmurs. A modified method of blind source component separation which uses a single sensor technique for signal separation was implemented. This technique benefits doctors to diagnose heart sounds while the patients express pain or agonies, without silencing them. The analysis was to find out whether heart sounds can be separated from speech frequencies. Here a trustworthy separation technique with improved level of clarity had been achieved.

Subject Classification: (2010):

• 94A99

Keywords:

• Blind source component separation
• W-disjoint orthogonality principle
• Maximum likelihood gradient search
• Single microphone approach