{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T21:53:09Z","timestamp":1785621189291,"version":"3.56.0"},"reference-count":34,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T00:00:00Z","timestamp":1560988800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Qatar National Research Foundation (QNRF)","award":["UREP19-069-2-031"],"award-info":[{"award-number":["UREP19-069-2-031"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>One of the major causes of death all over the world is heart disease or cardiac dysfunction. These diseases could be identified easily with the variations in the sound produced due to the heart activity. These sophisticated auscultations need important clinical experience and concentrated listening skills. Therefore, there is an unmet need for a portable system for the early detection of cardiac illnesses. This paper proposes a prototype model of a smart digital-stethoscope system to monitor patient\u2019s heart sounds and diagnose any abnormality in a real-time manner. This system consists of two subsystems that communicate wirelessly using Bluetooth low energy technology: A portable digital stethoscope subsystem, and a computer-based decision-making subsystem. The portable subsystem captures the heart sounds of the patient, filters and digitizes, and sends the captured heart sounds to a personal computer wirelessly to visualize the heart sounds and for further processing to make a decision if the heart sounds are normal or abnormal. Twenty-seven t-domain, f-domain, and Mel frequency cepstral coefficients (MFCC) features were used to train a public database to identify the best-performing algorithm for classifying abnormal and normal heart sound (HS). The hyper parameter optimization, along with and without a feature reduction method, was tested to improve accuracy. The cost-adjusted optimized ensemble algorithm can produce 97% and 88% accuracy of classifying abnormal and normal HS, respectively.<\/jats:p>","DOI":"10.3390\/s19122781","type":"journal-article","created":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T10:49:59Z","timestamp":1561027799000},"page":"2781","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":136,"title":["Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0744-8206","authenticated-orcid":false,"given":"Muhammad E.H.","family":"Chowdhury","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, Qatar University, Doha 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7068-9112","authenticated-orcid":false,"given":"Amith","family":"Khandakar","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, Qatar University, Doha 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khawla","family":"Alzoubi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, Qatar University, Doha 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samar","family":"Mansoor","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, Qatar University, Doha 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anas","family":"M. Tahir","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, Qatar University, Doha 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mamun Bin Ibne","family":"Reaz","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic &amp; Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor 43600, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nasser","family":"Al-Emadi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, Qatar University, Doha 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,20]]},"reference":[{"key":"ref_1","first-page":"e38","article-title":"Heart disease and stroke statistics\u20142016 update a report from the American Heart Association","volume":"133","author":"Mozaffarian","year":"2016","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1136\/heartjnl-2015-307516","article-title":"The epidemiology of cardiovascular disease in the UK 2014","volume":"101","author":"Bhatnagar","year":"2015","journal-title":"Heart"},{"key":"ref_3","unstructured":"Nichols, M., Peterson, K., Herbert, J., Alston, L., and Allender, S. 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