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Abstract: In 1992, Brockmeier et al. showed the difference in magnetocardiography (MCG)-detected field distribution generated by the heart at rest and under stress. Unfortunately, routinely recorded magnetocardiograms (MCGs) are corrupted by different types of artifacts, especially during stress. This work addressed the problem of optimizing artifacts removing and improving the signal to noise ratio (SNR) in patients with coronary heart disease (CHD) under pharmacological stress MCG (PSMCG) using a technique of Blind Source Separation (BSS) called TDSEP. Techniques based on simple statistical parameters were proposed to identify the cardiac related component among the unmixed data. The presented results showed that BSS could detect and remove a variety of noise and artifact sources in PSMCG, allowing the use in clinical applications. [Copyright &y& Elsevier]

Abstract: The field distribution generated by the heart and detected by magnetocardiography (MCG) shows strong effects, comparing the field distribution at rest and under stress. To study the possible clinical application, it is convenient to avoid pharmacological stress and perform Stress MCG (SMCG) using conventional physical stress with an ergometer. Unfortunately the subject movements and the ergometer residual artefacts produce extra noise and disturbances which should be eliminated. For this purpose 4 different Blind Source Separation (BSS) algorithms were tested: fastICA, TDSEP, JADE and SHIBBS. The algorithms were applied on 12 SMCG data sets for the task to de-noise them. The correlation between odd and even beats (using the simultaneously recorded electrocardiogram (ECG)) and the known spectral content were considered for automatically detecting noise and disturbances. All the methods were able to detect the ergometer noise. The best results were achieved by TDSEP, both in computation time and in goodness of separation. This work shows that, with BSS, the extraction of heart signals from ergometer SMCG data is becoming feasible. [Copyright &y& Elsevier]