{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T03:21:12Z","timestamp":1778642472418,"version":"3.51.4"},"reference-count":34,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,6,3]],"date-time":"2022-06-03T00:00:00Z","timestamp":1654214400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST 107-2622-E-239-003-CC3"],"award-info":[{"award-number":["MOST 107-2622-E-239-003-CC3"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["TCVGH-NUU1098901"],"award-info":[{"award-number":["TCVGH-NUU1098901"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["TCVGH-NUU1108901"],"award-info":[{"award-number":["TCVGH-NUU1108901"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Taichung Veterans General Hospital, Taiwan","award":["MOST 107-2622-E-239-003-CC3"],"award-info":[{"award-number":["MOST 107-2622-E-239-003-CC3"]}]},{"name":"Taichung Veterans General Hospital, Taiwan","award":["TCVGH-NUU1098901"],"award-info":[{"award-number":["TCVGH-NUU1098901"]}]},{"name":"Taichung Veterans General Hospital, Taiwan","award":["TCVGH-NUU1108901"],"award-info":[{"award-number":["TCVGH-NUU1108901"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With conventional stethoscopes, the auscultation results may vary from one doctor to another due to a decline in his\/her hearing ability with age or his\/her different professional training, and the problematic cardiopulmonary sound cannot be recorded for analysis. In this paper, to resolve the above-mentioned issues, an electronic stethoscope was developed consisting of a traditional stethoscope with a condenser microphone embedded in the head to collect cardiopulmonary sounds and an AI-based classifier for cardiopulmonary sounds was proposed. Different deployments of the microphone in the stethoscope head with amplification and filter circuits were explored and analyzed using fast Fourier transform (FFT) to evaluate the effects of noise reduction. After testing, the microphone placed in the stethoscope head surrounded by cork is found to have better noise reduction. For classifying normal (healthy) and abnormal (pathological) cardiopulmonary sounds, each sample of cardiopulmonary sound is first segmented into several small frames and then a principal component analysis is performed on each small frame. The difference signal is obtained by subtracting PCA from the original signal. MFCC (Mel-frequency cepstral coefficients) and statistics are used for feature extraction based on the difference signal, and ensemble learning is used as the classifier. The final results are determined by voting based on the classification results of each small frame. After the testing, two distinct classifiers, one for heart sounds and one for lung sounds, are proposed. The best voting for heart sounds falls at 5\u201345% and the best voting for lung sounds falls at 5\u201365%. The best accuracy of 86.9%, sensitivity of 81.9%, specificity of 91.8%, and F1 score of 86.1% are obtained for heart sounds using 2 s frame segmentation with a 20% overlap, whereas the best accuracy of 73.3%, sensitivity of 66.7%, specificity of 80%, and F1 score of 71.5% are yielded for lung sounds using 5 s frame segmentation with a 50% overlap.<\/jats:p>","DOI":"10.3390\/s22114263","type":"journal-article","created":{"date-parts":[[2022,6,3]],"date-time":"2022-06-03T08:01:18Z","timestamp":1654243278000},"page":"4263","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Development of an Electronic Stethoscope and a Classification Algorithm for Cardiopulmonary Sounds"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2821-2040","authenticated-orcid":false,"given":"Yu-Chi","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, National United University, Miaoli City 36003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chin-Chuan","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National United University, Miaoli City 36003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao-Shu","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Information Management, National United University, Miaoli City 36003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fu-Lin","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National United University, Miaoli City 36003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shi-Feng","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National United University, Miaoli City 36003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tsu-Yi","family":"Shieh","sequence":"additional","affiliation":[{"name":"Section of Clinical Training, Department of Medical Education, Taichung Veterans General Hospital, Taichung City 40705, Taiwan"},{"name":"Division of Allergy, Immunology and Rheumatology, Taichung Veterans General Hospital, Taichung City 40705, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8409-3237","authenticated-orcid":false,"given":"Hsian-Min","family":"Chen","sequence":"additional","affiliation":[{"name":"Center for Quantitative Imaging in Medicine (CQUIM), Department of Medical Research, Taichung Veterans General Hospital, Taichung City 40705, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin-Yuan","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National United University, Miaoli City 36003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2583","DOI":"10.1109\/JBHI.2021.3056916","article-title":"Design and Comparative Performance of a Robust Lung Auscultation System for Noisy Clinical Settings","volume":"25","author":"McLane","year":"2021","journal-title":"IEEE J. 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