Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography
Coronary artery disease (CAD) is the most common cause of death globally. Patients with suspected CAD are usually assessed by exercise electrocardiography (ECG). Subsequent tests, such as coronary angiography and coronary computed tomography angiography (CCTA) are performed to localize the stenosis...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-09-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fphys.2019.01211/full |
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| author | Parastoo Dehkordi Erwin P. Bauer Kouhyar Tavakolian Kouhyar Tavakolian Vahid Zakeri Andrew P. Blaber Farzad Khosrow-Khavar |
| author_facet | Parastoo Dehkordi Erwin P. Bauer Kouhyar Tavakolian Kouhyar Tavakolian Vahid Zakeri Andrew P. Blaber Farzad Khosrow-Khavar |
| author_sort | Parastoo Dehkordi |
| collection | DOAJ |
| description | Coronary artery disease (CAD) is the most common cause of death globally. Patients with suspected CAD are usually assessed by exercise electrocardiography (ECG). Subsequent tests, such as coronary angiography and coronary computed tomography angiography (CCTA) are performed to localize the stenosis and to estimate the degree of blockage. The present study describes a non-invasive methodology to identify patients with CAD based on the analysis of both rest and exercise seismocardiography (SCG). SCG is a non-invasive technology for capturing the acceleration of the chest induced by myocardial motion and vibrations. SCG signals were recorded from 185 individuals at rest and immediately after exercise. Two models were developed using the characterization of the rest and exercise SCG signals to identify individuals with CAD. The models were validated against related results from angiography. For the rest model, accuracy was 74%, and sensitivity and specificity were estimated as 75 and 72%, respectively. For the exercise model accuracy, sensitivity, and specificity were 81, 82, and 84%, respectively. The rest and exercise models presented a bootstrap-corrected area under the curve of 0.77 and 0.91, respectively. The discrimination slope was estimated 0.32 for rest model and 0.47 for the exercise model. The difference between the discrimination slopes of these two models was 0.15 (95% CI: 0.10 to 0.23, p < 0.0001). Both rest and exercise models are able to detect CAD with comparable accuracy, sensitivity, and specificity. Performance of SCG is better compared to stress-ECG and it is identical to stress-echocardiography and CCTA. SCG examination is fast, inexpensive, and may even be carried out by laypersons. |
| first_indexed | 2024-04-12T07:23:08Z |
| format | Article |
| id | doaj.art-d40646910c0e4604a9cf2164e2dca2d6 |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-04-12T07:23:08Z |
| publishDate | 2019-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-d40646910c0e4604a9cf2164e2dca2d62022-12-22T03:42:16ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2019-09-011010.3389/fphys.2019.01211472815Identifying Patients With Coronary Artery Disease Using Rest and Exercise SeismocardiographyParastoo Dehkordi0Erwin P. Bauer1Kouhyar Tavakolian2Kouhyar Tavakolian3Vahid Zakeri4Andrew P. Blaber5Farzad Khosrow-Khavar6Electrical and Computer Engineering Department, Biomedical Department, The University of British Columbia, Vancouver, BC, CanadaHeart Force Medical Inc., Vancouver, BC, CanadaSchool of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, United StatesBiomedical Physiology and Kinesiology Department, Simon Fraser University, Vancouver, BC, CanadaHeart Force Medical Inc., Vancouver, BC, CanadaBiomedical Physiology and Kinesiology Department, Simon Fraser University, Vancouver, BC, CanadaHeart Force Medical Inc., Vancouver, BC, CanadaCoronary artery disease (CAD) is the most common cause of death globally. Patients with suspected CAD are usually assessed by exercise electrocardiography (ECG). Subsequent tests, such as coronary angiography and coronary computed tomography angiography (CCTA) are performed to localize the stenosis and to estimate the degree of blockage. The present study describes a non-invasive methodology to identify patients with CAD based on the analysis of both rest and exercise seismocardiography (SCG). SCG is a non-invasive technology for capturing the acceleration of the chest induced by myocardial motion and vibrations. SCG signals were recorded from 185 individuals at rest and immediately after exercise. Two models were developed using the characterization of the rest and exercise SCG signals to identify individuals with CAD. The models were validated against related results from angiography. For the rest model, accuracy was 74%, and sensitivity and specificity were estimated as 75 and 72%, respectively. For the exercise model accuracy, sensitivity, and specificity were 81, 82, and 84%, respectively. The rest and exercise models presented a bootstrap-corrected area under the curve of 0.77 and 0.91, respectively. The discrimination slope was estimated 0.32 for rest model and 0.47 for the exercise model. The difference between the discrimination slopes of these two models was 0.15 (95% CI: 0.10 to 0.23, p < 0.0001). Both rest and exercise models are able to detect CAD with comparable accuracy, sensitivity, and specificity. Performance of SCG is better compared to stress-ECG and it is identical to stress-echocardiography and CCTA. SCG examination is fast, inexpensive, and may even be carried out by laypersons.https://www.frontiersin.org/article/10.3389/fphys.2019.01211/fullcoronary artery diseaseseismocardiography (SCG)electrocardiograph (ECG)exercise stress testheart mechanical activity |
| spellingShingle | Parastoo Dehkordi Erwin P. Bauer Kouhyar Tavakolian Kouhyar Tavakolian Vahid Zakeri Andrew P. Blaber Farzad Khosrow-Khavar Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography Frontiers in Physiology coronary artery disease seismocardiography (SCG) electrocardiograph (ECG) exercise stress test heart mechanical activity |
| title | Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography |
| title_full | Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography |
| title_fullStr | Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography |
| title_full_unstemmed | Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography |
| title_short | Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography |
| title_sort | identifying patients with coronary artery disease using rest and exercise seismocardiography |
| topic | coronary artery disease seismocardiography (SCG) electrocardiograph (ECG) exercise stress test heart mechanical activity |
| url | https://www.frontiersin.org/article/10.3389/fphys.2019.01211/full |
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