Detection of Cough and Adventitious Respiratory Sounds in Audio Recordings by Internal Sound Analysis



We present a multi-feature approach to the detection of cough and adventitious respiratory sounds. After the removal of near-silent segments, a vector of event boundaries is obtained and a proposed set of 126 features is extracted for each event. Evaluation was performed on a data set comprised of internal audio recordings from 18 patients. The best performance (F-measure = 0.69 +- 0.03; specificity = 0.90 +- 0.01) was achieved when merging wheezes and crackles into a single class of adventitious respiratory sounds.

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WELCOME - Wearable Sensing and Smart Cloud Computing for Integrated Care to COPD Patients with Comorbidities


International Conference on Biomedical and Health Informatics, November 2017

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