Abstract
It is an important branch of biometrics security to obtain the cardiomagnetic signal non-invasively. In our study, the problem of sparse cardiac current source reconstruction is studied using Bayesian matching pursuit with non-Gaussian prior. The characteristics of cardiac electrical activity by source imaging are analyzed. We use goodness of fit (GoF) and root mean square error (RMSE) to measure the reconstruction ability of the source reconstruction method. The trajectory during QRS complex and T-wave segment can preliminarily reveal the conduction features of electrical excitation and effective electrophysiological information in ventricular depolarization and repolarization. The experimental results verify that our method with the source solution non-Gaussian or unknown prior is available for cardiomagnetic signal’s inverse problem and cardiac sparse source imaging.
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Acknowledgment
The authors would like to express their gratitude to Prof. Shiqin Jiang, Ph.D Dafang Zhou, Ph.D Chen Zhao for academic exchange and great support during this project. The authors are also grateful to Shanghai Institute of Microsystem and Information Technology, for kindly providing the data. This work is supported by the Natural Science Foundation of Shanghai (Grant No. 18ZR1427400), the Shanghai Business School ‘Phosphor’ Science Foundation, and the Natural Science Foundation of Shanghai (Grant No. 18ZR1427500).
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Bing, L., Li, Y., Si, W. (2020). Noninvasive Research on Cardiac Electrical Activity by Non-Gaussian Prior Bayesian Matching Pursuit. In: Xu, G., Liang, K., Su, C. (eds) Frontiers in Cyber Security. FCS 2020. Communications in Computer and Information Science, vol 1286. Springer, Singapore. https://doi.org/10.1007/978-981-15-9739-8_9
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DOI: https://doi.org/10.1007/978-981-15-9739-8_9
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