An Automated Computerized Auscultation and Diagnostic System for Pulmonary Diseases
Abbas A et al. - The research focuses on developing an automated auscultation diagnostic system that overcomes the limitations inherent in traditional auscultation techniques. The system uses a front end sound signal filtering module that uses adaptive Neural Networks (NN) noise cancellation to eliminate spurious sound signals like those from the heart, intestine, and ambient noise. To date, the core diagnosis module is capable of identifying lung sounds from non-lung sounds, normal lung sounds from abnormal ones, and identifying wheezes from crackles as indicators of different ailments. [more...]
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