{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T04:19:29Z","timestamp":1792815569609,"version":"4.5.0"},"reference-count":55,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T00:00:00Z","timestamp":1616716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004530","name":"Universiti Putra Malaysia","doi-asserted-by":"publisher","award":["UPM-IPS"],"award-info":[{"award-number":["UPM-IPS"]}],"id":[{"id":"10.13039\/501100004530","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Malaysian Ministry of Higher Education","award":["PRGS"],"award-info":[{"award-number":["PRGS"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle death (known as myocardial infarction). The electrocardiogram (ECG) reflects these cardiac condition changes as electrical signals. However, an accurate interpretation of these waveforms still calls for the expertise of an experienced cardiologist. Several algorithms have been developed to overcome issues in this area. In this study, a new scheme for myocardial ischemia detection with multi-lead long-interval ECG is proposed. This scheme involves an observation of the changes in ischemic-related ECG components (ST segment and PR segment) by way of the Choi-Williams time-frequency distribution to extract ST and PR features. These extracted features are mapped to a multi-class SVM classifier for training in the detection of unknown conditions to determine if they are normal or ischemic. The use of multi-lead ECG for classification and 1 min intervals instead of beats or frames contributes to improved detection performance. The classification process uses the data of 92 normal and 266 patients from four different databases. The proposed scheme delivered an overall result with 99.09% accuracy, 99.49% sensitivity, and 98.44% specificity. The high degree of classification accuracy for the different and unknown data sources used in this study reflects the flexibility, validity, and reliability of this proposed scheme. Additionally, this scheme can assist cardiologists in detecting signal abnormality with robustness and precision, and can even be used for home screening systems to provide rapid evaluation in emergency cases.<\/jats:p>","DOI":"10.3390\/s21072311","type":"journal-article","created":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T06:59:42Z","timestamp":1616741982000},"page":"2311","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2483-0028","authenticated-orcid":false,"given":"Ahmed Faeq","family":"Hussein","sequence":"first","affiliation":[{"name":"Biomedical Engineering Department, Faculty of Engineering, Al-Nahrain University, Baghdad 10072, Iraq"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaiful Jahari","family":"Hashim","sequence":"additional","affiliation":[{"name":"Department of Computer &amp; Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fakhrul Zaman","family":"Rokhani","sequence":"additional","affiliation":[{"name":"Department of Computer &amp; Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wan Azizun","family":"Wan Adnan","sequence":"additional","affiliation":[{"name":"Department of Computer &amp; Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e121","DOI":"10.1161\/STROKEAHA.115.008097","article-title":"Organizational update: The world health organization global status report on noncommunicable diseases 2014; one more landmark step in the combat against stroke and vascular disease","volume":"46","author":"Mendis","year":"2015","journal-title":"Stroke"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1007\/s00038-020-01443-x","article-title":"Holiday and weekend effects on mortality for acute myocardial infarction in Shanxi, China: A cross-sectional study","volume":"65","author":"Lin","year":"2020","journal-title":"Int. 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