{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T10:28:14Z","timestamp":1780396094444,"version":"3.54.1"},"reference-count":49,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,5,21]],"date-time":"2021-05-21T00:00:00Z","timestamp":1621555200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62071277"],"award-info":[{"award-number":["62071277"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61501280"],"award-info":[{"award-number":["61501280"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61471223"],"award-info":[{"award-number":["61471223"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61601263"],"award-info":[{"award-number":["61601263"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Heart sound signals reflect valuable information about heart condition. Previous studies have suggested that the information contained in single-channel heart sound signals can be used to detect coronary artery disease (CAD). But accuracy based on single-channel heart sound signal is not satisfactory. This paper proposed a method based on multi-domain feature fusion of multi-channel heart sound signals, in which entropy features and cross entropy features are also included. A total of 36 subjects enrolled in the data collection, including 21 CAD patients and 15 non-CAD subjects. For each subject, five-channel heart sound signals were recorded synchronously for 5 min. After data segmentation and quality evaluation, 553 samples were left in the CAD group and 438 samples in the non-CAD group. The time-domain, frequency-domain, entropy, and cross entropy features were extracted. After feature selection, the optimal feature set was fed into the support vector machine for classification. The results showed that from single-channel to multi-channel, the classification accuracy has increased from 78.75% to 86.70%. After adding entropy features and cross entropy features, the classification accuracy continued to increase to 90.92%. The study indicated that the method based on multi-domain feature fusion of multi-channel heart sound signals could provide more information for CAD detection, and entropy features and cross entropy features played an important role in it.<\/jats:p>","DOI":"10.3390\/e23060642","type":"journal-article","created":{"date-parts":[[2021,5,21]],"date-time":"2021-05-21T13:15:15Z","timestamp":1621602915000},"page":"642","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals"],"prefix":"10.3390","volume":"23","author":[{"given":"Tongtong","family":"Liu","sequence":"first","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4684-4909","authenticated-orcid":false,"given":"Peng","family":"Li","sequence":"additional","affiliation":[{"name":"Division of Sleep and Circadian Disorders, Brigham and Women\u2019s Hospital, Boston, MA 02115, USA"},{"name":"Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3223-8286","authenticated-orcid":false,"given":"Huan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China"},{"name":"Department of Medical Engineering, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Jiao","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changchun","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chandan","family":"Karmakar","sequence":"additional","affiliation":[{"name":"School of Information Technology, Deakin University, Geelong, VIC 3225, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohong","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengli","family":"Ren","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2981-7957","authenticated-orcid":false,"given":"Xinpei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e56","DOI":"10.1161\/CIR.0000000000000659","article-title":"Heart disease and stroke statistics-2019 update: A report from the American heart association","volume":"139","author":"Benjamin","year":"2019","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.1093\/ndt\/gfi328","article-title":"Investigation of coronary artery calcification and stenosis by coronary angiography (CAG) in haemodialysis patients","volume":"21","author":"Yoshida","year":"2006","journal-title":"Nephrol. Dial. Transplant."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1146\/annurev.bioeng.9.060906.151840","article-title":"Acoustic detection of coronary artery disease","volume":"9","author":"Semmlow","year":"2007","journal-title":"Annu. Rev. Biomed. Eng."},{"key":"ref_4","unstructured":"Mahnke, C. (2009, January 2\u20136). Automated heartsound analysis\/computer-aided auscultation: A cardiologist\u2019s perspective and suggestions for future development. Proceedings of the 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, Minnesota."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1109\/10.237677","article-title":"Noninvasive acoustical detection of coronary artery disease: A comparative study of signal processing methods","volume":"40","author":"Akay","year":"1993","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1109\/TBME.1983.325211","article-title":"Coronary artery disease\u2014Correlates between diastolic auditory characteristics and coronary artery stenoses","volume":"2","author":"Semmlow","year":"1983","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s10554-015-0753-4","article-title":"Diagnosing coronary artery disease by sound analysis from coronary stenosis induced turbulent blood flow: Diagnostic performance in patients with stable angina pectoris","volume":"32","author":"Winther","year":"2016","journal-title":"Int. J. Cardiovasc. Imaging"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1136\/heartjnl-2017-311944","article-title":"Diagnostic performance of an acoustic-based system for coronary artery disease risk stratification","volume":"104","author":"Winther","year":"2018","journal-title":"Heart"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2611","DOI":"10.1109\/TBME.2015.2432129","article-title":"Acoustic features for the identification of coronary artery disease","volume":"62","author":"Schmidt","year":"2015","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Gauthier, D., Akay, Y.M., Paden, R.G., Pavlicek, W., and Akay, M. (2007, January 8\u201311). Spectral Analysis of Heart Sounds Associated with Coronary Occlusions. Proceedings of the 2007 6th International Special Topic Conference on Information Technology Applications in Biomedicine, Tokyo, Japan.","DOI":"10.1109\/ITAB.2007.4407421"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zhao, Z.D., and Wang, Y. (2007, January 19\u201322). Analysis of Diastolic Murmurs for Coronary artery Diseasebased on hilbert Huang Transform. Proceedings of the 2007 International Conference on Machine Learning and Cybernetics, Hong Kong, China.","DOI":"10.1109\/ICMLC.2007.4370724"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"8019","DOI":"10.1016\/j.eswa.2010.05.088","article-title":"Detection of cardiac abnormality from PCG signal using LMS based least square SVM classifier","volume":"37","author":"Ari","year":"2010","journal-title":"Expert Syst. Appl."},{"key":"ref_13","first-page":"157","article-title":"Nonlinear analysis of diastolic heart sounds based on EMD and correlation dimension","volume":"172","author":"Zhao","year":"2014","journal-title":"Sens. Transducers"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/TBME.2008.2003098","article-title":"Dynamics of diastolic sounds caused by partially occluded coronary arteries","volume":"56","author":"Akay","year":"2009","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Griffel, B., Zia, M.K., Fridman, V., Saponieri, C., and Semmlow, J.L. (2011, January 1\u20133). Microphone placement evaluation for acoustic detection of coronary artery disease. Proceedings of the 2011 IEEE 37th Annual Northeast Bioengineering Conference (NEBEC), Troy, NY, USA.","DOI":"10.1109\/NEBC.2011.5778616"},{"key":"ref_16","unstructured":"Samanta, P., Mandana, K., and Saha, G. (2017, January 15\u201317). Identification of coronary artery disease using cross power spectral density. Proceedings of the 2017 14th IEEE India Council International Conference (INDICON), Roorkee, India."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"101688","DOI":"10.1016\/j.bspc.2019.101688","article-title":"Classification and evaluation of the severity of tricuspid regurgitation using phonocardiogram","volume":"57","author":"Rujoie","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"107242","DOI":"10.1016\/j.apacoust.2020.107242","article-title":"An improved method to detect coronary artery disease using phonocardiogram signals in noisy environment","volume":"164","author":"Pathak","year":"2020","journal-title":"Appl. Acoust."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s13239-012-0094-6","article-title":"Detection of coronary artery disease using automutual information","volume":"3","author":"Griffel","year":"2012","journal-title":"Cardiovasc. Eng. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"H2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy","volume":"278","author":"Richman","year":"2000","journal-title":"Am. J. Physiology. Heart Circ. Physiol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Tang, H., Jiang, Y., Li, T., and Wang, X. (2018). Identification of pulmonary hypertension using entropy measure analysis of heart sound signal. Entropy, 20.","DOI":"10.3390\/e20050389"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1186\/1475-925X-13-73","article-title":"Effects of acute hypoxia on heart rate variability, sample entropy and cardiorespiratory phase synchronization","volume":"13","author":"Zhang","year":"2014","journal-title":"Biomed. Eng. Online"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s11517-014-1216-0","article-title":"Assessing the complexity of short-term heartbeat interval series by distribution entropy","volume":"53","author":"Li","year":"2015","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Udhayakumar, R.K., Karmakar, C., Li, P., and Palaniswami, M. (2015, January 25\u201329). Effect of data length and bin numbers on distribution entropy (DistEn) measurement in analyzing healthy aging. Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy.","DOI":"10.1109\/EMBC.2015.7320218"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Shi, B., Motin, M.A., Wang, X., Karmakar, C., and Li, P. (2020). Bivariate Entropy Analysis of Electrocardiographic RR-QT Time Series. Entropy, 22.","DOI":"10.3390\/e22121439"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1715","DOI":"10.1016\/j.ins.2010.01.004","article-title":"Cross-fuzzy entropy: A new method to test pattern synchrony of bivariate time series","volume":"180","author":"Xie","year":"2010","journal-title":"Inf. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2231","DOI":"10.1109\/TBME.2016.2515543","article-title":"Detection of Coupling in Short Physiological Series by a Joint Distribution Entropy Method","volume":"63","author":"Li","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_28","unstructured":"Oppenheim, A.V., and Schafer, R.W. (1989). Discrete-Time Signal Processing, Prentice Hall."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1166\/jmihi.2020.2926","article-title":"Heart sound signal quality assessment based on multi-domain features","volume":"10","author":"Jiao","year":"2020","journal-title":"J. Med Imaging Health Inform."},{"key":"ref_30","first-page":"822","article-title":"Logistic regression-HSMM-based heart sound segmentation","volume":"63","author":"Springer","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_31","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":"ref_32","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1109\/10.61034","article-title":"Modeling sound generation in stenosed coronary arteries","volume":"37","author":"Wang","year":"1990","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"115007","DOI":"10.1088\/1361-6579\/abc323","article-title":"Detection of coronary artery disease using multi-modal feature fusion and hybrid feature selection","volume":"41","author":"Zhang","year":"2020","journal-title":"Physiol. Meas."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1109\/TNSRE.2007.897025","article-title":"Characterization of Surface EMG Signal Based on Fuzzy Entropy","volume":"15","author":"Chen","year":"2007","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Castiglioni, P., and Rienzo, M.D. (2008, January 14\u201317). How the Threshold \u201cr\u201d Influences Approximate Entropy Analysis of Heart-Rate Variability. Proceedings of the 2008 Computers in Cardiology, Bologna, Italy.","DOI":"10.1109\/CIC.2008.4749103"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.medengphy.2008.04.005","article-title":"Measuring complexity using FuzzyEn, ApEn, and SampEn","volume":"31","author":"Chen","year":"2008","journal-title":"Med Eng. Phys."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1063\/1.1554136","article-title":"Synchronization: A universal concept in nonlinear science","volume":"56","author":"Strogatz","year":"2003","journal-title":"Phys. Today"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.bspc.2015.05.005","article-title":"Measuring synchronization in coupled simulation and coupled cardiovascular time series: A comparison of different cross entropy measures","volume":"21","author":"Liu","year":"2015","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_39","first-page":"1","article-title":"Choice of link and variance function for generalized linear mixed models: A case study with binomial response in proteomics","volume":"49","author":"Malik","year":"2019","journal-title":"Commun. Stat. Theory Methods"},{"key":"ref_40","unstructured":"Yang, Y., and Pedersen, J.O. (1997, January 8\u201312). A Comparative Study on Feature Selection in Text Categorization. Proceedings of the Fourteenth International Conference on Machine Learning, Nashville, TN, USA."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"19","DOI":"10.3389\/fnbot.2017.00019","article-title":"Cross-subject EEG feature selection for emotion recognition using transfer recursive feature elimination","volume":"11","author":"Yin","year":"2017","journal-title":"Front. Neurorobot."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.cmpb.2016.10.011","article-title":"Automated Diagnosis of Coronary Artery Disease (CAD) Patients Using Optimized SVM","volume":"138","author":"Davari","year":"2016","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2182","DOI":"10.1016\/j.eswa.2009.07.055","article-title":"Effects of principle component analysis on assessment of coronary artery diseases using support vector machine","volume":"37","author":"Bayrak","year":"2010","journal-title":"Expert Syst. Appl."},{"key":"ref_45","first-page":"53","article-title":"The concept of sensitivity and specificity in relation to two types of errors and its application in medical research","volume":"2","author":"Sharma","year":"2009","journal-title":"Math. Ences Res. J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"4205027","DOI":"10.1155\/2018\/4205027","article-title":"PCG classification using multidomain features and SVM classifier","volume":"2018","author":"Tang","year":"2018","journal-title":"BioMed Res. Int."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"893","DOI":"10.7863\/jum.2007.26.7.893","article-title":"Tissue Synchronization Imaging of Myocardial Dyssynchronicity of the Left Ventricle in Patients with Coronary Artery Disease","volume":"26","author":"Tian","year":"2007","journal-title":"J. Ultrasound Med."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0002-9149(73)80130-4","article-title":"Myocardial function during atrial pacing in patients with angina pectoris and normal coronary arteriograms: Comparison with patients having significant coronary artery disease","volume":"32","author":"Arbogast","year":"1973","journal-title":"Am. J. Cardiol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1136\/hrt.2003.020594","article-title":"Angina pectoris and normal coronary arteries: Cardiac syndrome X","volume":"90","author":"Crea","year":"2004","journal-title":"Heart"}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/23\/6\/642\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:05:28Z","timestamp":1760162728000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/23\/6\/642"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,21]]},"references-count":49,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["e23060642"],"URL":"https:\/\/doi.org\/10.3390\/e23060642","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,21]]}}}