{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T05:03:03Z","timestamp":1667278983606},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683461","type":"print"},{"value":"9781643683478","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T00:00:00Z","timestamp":1666051200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,18]]},"abstract":"<jats:p>Topological data analysis (TDA) method could catch the rich geometric and topologic information of big data and find subtle differences between different signals. TDA method opens up a new way for biomedical data analysis. In this study, we applied TDA method for heart sound signals (PCG) classification. First, the sliding window method was used to build a point cloud. Then, the persistent barcode is extracted from the point cloud by using the topology technology Vietoris-Rips (VR) filtration. At last, GoogLeNet transfer learning model was applied for classifing. The proposed the model did work well on the 2016 PhysioNet\/CinC challenge dataset, Se=99.30%, +P=99.57%, F1=99.44%, mAcc=99.47%. The results showed that TDA can be used for the analysis of physiological signals in large quantities. The proposed method in this study has opened a new space for the application of TDA methods in physiological signal analysis.<\/jats:p>","DOI":"10.3233\/faia220409","type":"book-chapter","created":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T09:32:49Z","timestamp":1667208769000},"source":"Crossref","is-referenced-by-count":0,"title":["Classification of Heart Sounds Based on Topological Data Analysis Method"],"prefix":"10.3233","author":[{"given":"Feifei","family":"Liu","sequence":"first","affiliation":[{"name":"School of Science, Shandong Jianzhu University, Jinan, 250101, China"}]},{"given":"Yonglian","family":"Ren","sequence":"additional","affiliation":[{"name":"School of Science, Shandong Jianzhu University, Jinan, 250101, China"}]},{"given":"Shengxiang","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Science, Shandong Jianzhu University, Jinan, 250101, China"}]},{"given":"Qingli","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Science, Shandong Jianzhu University, Jinan, 250101, China"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Science and Technology, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China"}]},{"given":"Ziyu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Science, Shandong Jianzhu University, Jinan, 250101, China"}]},{"given":"Zheng","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Science, Shandong Jianzhu University, Jinan, 250101, China"}]},{"given":"Sen","family":"Ai","sequence":"additional","affiliation":[{"name":"School of Science, Shandong Jianzhu University, Jinan, 250101, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining VIII"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220409","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T09:32:50Z","timestamp":1667208770000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220409"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,18]]},"ISBN":["9781643683461","9781643683478"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220409","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,18]]}}}