Exercise Seismocardiography for Detection of Coronary Artery Disease

Abstract

Seismocardiography is a noninvasive test being studied for use in conjunction with standard exercise testing to detect changes in cardiac function as a result of exercise-induced ischemia. To test the ability of exercise seismocardiography to detect coronary artery disease, exercise seismocardiograms were recorded on 1,221 patients undergoing routine exercise testing. From these, 204 patients were analyzed who had either coronary angiography or an estimated <2% risk of coronary disease. Sensitivity for detection of > 50% coronary artery stenosis was 67% for electrocardiography and 80% for seismocardiography (p < 0.01). Specificity was 51 % for electrocardiography and 69% for seismocardiography (p < 0.02). When both tests were abnormal, their positive predictive value was 88%. When both tests were normal, their negative predictive value was 80%. Exercise seismocardiography provided an easy, rapid adjunct to exercise electrocardiography for detection of coronary artery disease in this study.

Usefulness of Seismocardiography for the Diagnosis of Ischemia in Patients with Coronary Artery Disease

“…9 Taking into account the cut points on the score (S), we can trace the predictive value receiver operating characteristics curve (pv-ROC) plotting the positive predictive value against: 100 − negative predictive value. Moreover, we created a severity score (S) based on the number of arteries n i with percent occlusion indicated by i (i = 1, 2, 3, 4 for levels of occlusion so that S = i n i 4 (i−1) ).…”

“…[1][2][3][4][5][6][7][8][9][10] SCG is used in conjunction with exercise stress test (ETT) and is useful for the detection of exerciseinduced changes in cardiac muscle contractility that may occur during myocardial ischemia. He realized that the sophisticated technology developed in the 1980s during earthquakes study-seismology-could be applied to cardiology.…”

<title>Applications of neural networks to the radarcardiogram (RCG)</title>

“…Substituting this result into (8) we get s(t) = C(Re(J, (f3)Jfl2lt ) cos a -Im(J ($)eP2t ) sina) (10) = C(J ($)COS(27flfmt)COSa -,iJn (/3) S1fl(27flfmt) sina) (11) Finally, using the trigonometric angle-sum relationship we obtain s(t) = C J (f3)COS(2itflfmt + a) (12) which is the desired result. Substituting this result into (8) we get s(t) = C(Re(J, (f3)Jfl2lt ) cos a -Im(J ($)eP2t ) sina) (10) = C(J ($)COS(27flfmt)COSa -,iJn (/3) S1fl(27flfmt) sina) (11) Finally, using the trigonometric angle-sum relationship we obtain s(t) = C J (f3)COS(2itflfmt + a) (12) which is the desired result.…”

A Wearable Patch to Enable Long-Term Monitoring of Environmental, Activity and Hemodynamics Variables

“…The SCG signal was first shown to be useful in enhancing the diagnostic capability of exercise stress testing for coronary artery disease (CAD) in 1992 [16], and then subsequently demonstrated as capable of evaluating exercise capacity for sports medicine [17]. Furthermore, the results of a large multicenter study demonstrated that combining SCG and ECG signals improved the predictive accuracy of detecting CAD compared to using ECG alone [18].…”