{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T23:04:06Z","timestamp":1784243046244,"version":"3.55.0"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100011635","name":"Chinese Academy of Medical Sciences Fuwai Hospital","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011635","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010971","name":"Yunnan Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010971","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.bspc.2026.111005","type":"journal-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T08:46:36Z","timestamp":1784105196000},"page":"111005","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["Multi-classification algorithm of heart sounds for congenital heart disease based on Mel-scaled Frequency-domain Polynomial Chirplet Transform"],"prefix":"10.1016","volume":"127","author":[{"given":"Yanxiong","family":"Cheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongzhuo","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongbo","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhai","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2094-1671","authenticated-orcid":false,"given":"Pengfei","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7897-9787","authenticated-orcid":false,"given":"Weilian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"21","key":"10.1016\/j.bspc.2026.111005_b1","doi-asserted-by":"crossref","first-page":"2241","DOI":"10.1016\/j.jacc.2011.08.025","article-title":"Birth prevalence of congenital heart disease worldwide: a systematic review and meta-analysis","volume":"58","author":"Van Der Linde","year":"2011","journal-title":"J. Am. Coll. Cardiol."},{"issue":"7","key":"10.1016\/j.bspc.2026.111005_b2","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s10654-020-00653-0","article-title":"Birth prevalence of congenital heart disease in China, 1980\u20132019: a systematic review and meta-analysis of 617 studies","volume":"35","author":"Zhao","year":"2020","journal-title":"Eur. J. Epidemiol."},{"issue":"04","key":"10.1016\/j.bspc.2026.111005_b3","first-page":"269","article-title":"Interpretation of the annual report on cardiovascular health and diseases in China 2020","volume":"2","author":"of the Annual Report on Cardiovascular Health","year":"2022","journal-title":"Cardiol. Discov."},{"key":"10.1016\/j.bspc.2026.111005_b4","article-title":"Asthma prevalence based on the Baidu index and China\u2019s Health Statistical Yearbook from 2011 to 2020 in China","volume":"11","author":"Li","year":"2023","journal-title":"Front. Public Health"},{"issue":"3","key":"10.1016\/j.bspc.2026.111005_b5","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S2352-4642(19)30402-X","article-title":"Global, regional, and national burden of congenital heart disease, 1990\u20132017: a systematic analysis for the Global Burden of Disease Study 2017","volume":"4","author":"Zimmerman","year":"2020","journal-title":"Lancet Child Adolesc. Health"},{"key":"10.1016\/j.bspc.2026.111005_b6","series-title":"Textbook of Clinical Echocardiography","author":"Otto","year":"2013"},{"key":"10.1016\/j.bspc.2026.111005_b7","series-title":"Visual Guide to Neonatal Cardiology","author":"Alboliras","year":"2018"},{"issue":"1","key":"10.1016\/j.bspc.2026.111005_b8","doi-asserted-by":"crossref","first-page":"79","DOI":"10.2214\/ajr.127.1.79","article-title":"Computed tomography of the heart","volume":"127","author":"Ter-Pogossian","year":"1976","journal-title":"Am. J. Roentgenol."},{"issue":"3","key":"10.1016\/j.bspc.2026.111005_b9","doi-asserted-by":"crossref","first-page":"487","DOI":"10.2214\/AJR.14.13546","article-title":"CT myocardial perfusion imaging","volume":"204","author":"Varga-Szemes","year":"2015","journal-title":"Am. J. Roentgenol."},{"issue":"6","key":"10.1016\/j.bspc.2026.111005_b10","doi-asserted-by":"crossref","first-page":"303","DOI":"10.3109\/03091902.2012.684831","article-title":"A review of signal processing techniques for heart sound analysis in clinical diagnosis","volume":"36","author":"Emmanuel","year":"2012","journal-title":"J. Med. Eng. Technol."},{"issue":"9","key":"10.1016\/j.bspc.2026.111005_b11","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1009361","article-title":"Hemodynamics-driven mathematical model of first and second heart sound generation","volume":"17","author":"Shahmohammadi","year":"2021","journal-title":"PLoS Comput. Biol."},{"key":"10.1016\/j.bspc.2026.111005_b12","series-title":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference","first-page":"1","article-title":"Automatic heart and lung sounds classification using convolutional neural networks","author":"Chen","year":"2016"},{"issue":"7","key":"10.1016\/j.bspc.2026.111005_b13","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1007\/s00521-011-0610-x","article-title":"Adaptive neuro-fuzzy inference system for diagnosis of the heart valve diseases using wavelet transform with entropy","volume":"21","author":"U\u011fuz","year":"2012","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.bspc.2026.111005_b14","series-title":"2016 Computing in Cardiology Conference","first-page":"613","article-title":"Heart sound anomaly and quality detection using ensemble of neural networks without segmentation","author":"Zabihi","year":"2016"},{"issue":"12","key":"10.1016\/j.bspc.2026.111005_b15","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.1088\/0967-3334\/37\/12\/2181","article-title":"An open access database for the evaluation of heart sound algorithms","volume":"37","author":"Liu","year":"2016","journal-title":"Physiol. Meas."},{"key":"10.1016\/j.bspc.2026.111005_b16","series-title":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society","first-page":"168","article-title":"Rheumatic heart disease detection using deep learning from spectro-temporal representation of un-segmented heart sounds","author":"Asmare","year":"2020"},{"issue":"21","key":"10.1016\/j.bspc.2026.111005_b17","doi-asserted-by":"crossref","first-page":"4819","DOI":"10.3390\/s19214819","article-title":"Heartbeat sound signal classification using deep learning","volume":"19","author":"Raza","year":"2019","journal-title":"Sensors"},{"issue":"6","key":"10.1016\/j.bspc.2026.111005_b18","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1007\/s11760-018-1261-5","article-title":"Phonocardiogram signals processing approach for PASCAL classifying heart sounds challenge","volume":"12","author":"Chakir","year":"2018","journal-title":"Signal Image Video Process."},{"key":"10.1016\/j.bspc.2026.111005_b19","series-title":"2021 IEEE 7th International Conference on Cloud Computing and Intelligent Systems","first-page":"265","article-title":"A heart sound classification method based on time series analysis","author":"Chen","year":"2021"},{"key":"10.1016\/j.bspc.2026.111005_b20","series-title":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing","first-page":"1","article-title":"Heart sound classification using residual neural network and convolution block attention module","author":"Frimpong","year":"2022"},{"key":"10.1016\/j.bspc.2026.111005_b21","series-title":"2022 IEEE International Conference on Big Data","first-page":"2800","article-title":"Classification of heart sound using tunable Q wavelet transform and machine learning","author":"Thakur","year":"2022"},{"key":"10.1016\/j.bspc.2026.111005_b22","series-title":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers","first-page":"1026","article-title":"Abnormal heart sound detection by using temporal convolutional network","author":"Liu","year":"2022"},{"key":"10.1016\/j.bspc.2026.111005_b23","series-title":"2020 5th International Conference on Computing, Communication and Security","first-page":"1","article-title":"Multi-class heart sounds classification using 2D-convolutional neural network","author":"Banerjee","year":"2020"},{"key":"10.1016\/j.bspc.2026.111005_b24","series-title":"2022 7th International Conference on Intelligent Computing and Signal Processing","first-page":"8","article-title":"Heart sound classification method based on ensemble learning","author":"Chen","year":"2022"},{"key":"10.1016\/j.bspc.2026.111005_b25","series-title":"2022 3rd International Conference for Emerging Technology","first-page":"1","article-title":"Retracted: Multi-class classification and prediction of heart sounds using stacked LSTM to detect heart sound abnormalities","author":"Kamepalli","year":"2022"},{"key":"10.1016\/j.bspc.2026.111005_b26","series-title":"2022 Medical Technologies Congress","first-page":"1","article-title":"Automatic classification of diseases from heart sounds","author":"Demirci","year":"2022"},{"issue":"5","key":"10.1016\/j.bspc.2026.111005_b27","first-page":"959","article-title":"The diagnosis for the extrasystole heart sound signals based on the deep learning","volume":"8","author":"Chen","year":"2018","journal-title":"J. Med. Imaging Health Inform."},{"issue":"7","key":"10.1016\/j.bspc.2026.111005_b28","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1080\/03091902.2019.1576789","article-title":"Phonocardiogram classification using deep neural networks and weighted probability comparisons","volume":"42","author":"Sotaquir\u00e1","year":"2018","journal-title":"J. Med. Eng. Technol."},{"key":"10.1016\/j.bspc.2026.111005_b29","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.asoc.2019.01.019","article-title":"Applying an ensemble convolutional neural network with Savitzky\u2013Golay filter to construct a phonocardiogram prediction model","volume":"78","author":"Wu","year":"2019","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.bspc.2026.111005_b30","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.compbiomed.2018.06.026","article-title":"A study of time-frequency features for CNN-based automatic heart sound classification for pathology detection","volume":"100","author":"Bozkurt","year":"2018","journal-title":"Comput. Biol. Med."},{"issue":"9","key":"10.1016\/j.bspc.2026.111005_b31","doi-asserted-by":"crossref","first-page":"3222","DOI":"10.1109\/TIM.2011.2124770","article-title":"Polynomial chirplet transform with application to instantaneous frequency estimation","volume":"60","author":"Peng","year":"2011","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"1","key":"10.1016\/j.bspc.2026.111005_b32","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.ymssp.2014.01.002","article-title":"Frequency-varying group delay estimation using frequency domain polynomial chirplet transform","volume":"46","author":"Yang","year":"2014","journal-title":"Mech. Syst. Signal Process."},{"issue":"1","key":"10.1016\/j.bspc.2026.111005_b33","doi-asserted-by":"crossref","DOI":"10.1155\/2020\/8843963","article-title":"Deep layer kernel sparse representation network for the detection of heart valve ailments from the time-frequency representation of PCG recordings","volume":"2020","author":"Ghosh","year":"2020","journal-title":"BioMed Res. Int."},{"issue":"12","key":"10.1016\/j.bspc.2026.111005_b34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LSENS.2019.2949170","article-title":"Automated detection of heart valve disorders from the PCG signal using time-frequency magnitude and phase features","volume":"3","author":"Ghosh","year":"2019","journal-title":"IEEE Sens. Lett."},{"issue":"6","key":"10.1016\/j.bspc.2026.111005_b35","doi-asserted-by":"crossref","first-page":"3078","DOI":"10.1109\/JSEN.2019.2956072","article-title":"Time-frequency domain deep convolutional neural network for the classification of focal and non-focal EEG signals","volume":"20","author":"Madhavan","year":"2019","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.bspc.2026.111005_b36","doi-asserted-by":"crossref","unstructured":"H. Jin, Q. Song, X. Hu, Auto-keras: An efficient neural architecture search system, in: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019, pp. 1946\u20131956.","DOI":"10.1145\/3292500.3330648"}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426015594?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426015594?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T22:06:35Z","timestamp":1784239595000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426015594"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":36,"alternative-id":["S1746809426015594"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.111005","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Multi-classification algorithm of heart sounds for congenital heart disease based on Mel-scaled Frequency-domain Polynomial Chirplet Transform","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.111005","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"111005"}}