Electrocardiogram (ECG) acquisition is still a challenge as gradient artefacts superimposed on the electrophysiological signal can only be partially removed. The signal shape of theses artefacts can be similar to the QRS-complex, causing possible misinterpretation during patient monitoring and false triggering/gating of the MRI. For their real-time suppression, an adaptive filter is proposed. The adaptive filter is based on the noise-canceller configuration with LMS coefficient updates. The references of the noise canceller are the three gradient signals that are acquired simultaneously with the noisy ECG. Tests were done on patients, on volunteers and using an MR-safe ECG simulator. The noise canceller's performance was measured offline, simulating real-time processing by point-by-point operations. To create worst-case scenarios, clinical sequences with strong- and fast-switching gradients have been chosen. The noise-cancelling filter reduces the gradient artefacts' peak amplitudes by 80-99% after adaptation, without changing the desired ECG signal shape. The estimated reduction of total average power of the MR gradient artefacts is 62-98%. The proposed filter is capable of reducing artefacts due to strong- and fast-switching gradients in real-time applications and worst-case situations. The quality of the ECG is sufficiently high that a standard one-lead QRS-detector can be used for gating/triggering the MRI. For permanent patient monitoring, further improvements are needed.

This paper presents a bench study on a commercial automated external defibrillator (AED). The objective was to evaluate the performance of the defibrillation advisory system and its robustness against electromagnetic interferences (EMI) with central frequencies of 16.7, 50 and 60 Hz. The shock advisory system uses two 50 and 60 Hz band-pass filters, an adaptive filter to identify and suppress 16.7 Hz interference, and a software technique for arrhythmia analysis based on morphology and frequency ECG parameters. The testing process includes noise-free ECG strips from the internationally recognized MIT-VFDB ECG database that were superimposed with simulated EMI artifacts and supplied to the shock advisory system embedded in a real AED. Measurements under special consideration of the allowed variation of EMI frequency (15.7-17.4, 47-52, 58-62 Hz) and amplitude (1 and 8 mV) were performed to optimize external validity. The accuracy was reported using the American Heart Association (AHA) recommendations for arrhythmia analysis performance. In the case of artifact-free signals, the AHA performance goals were exceeded for both sensitivity and specificity: 99% for ventricular fibrillation (VF), 98% for rapid ventricular tachycardia (VT), 90% for slow VT, 100% for normal sinus rhythm, 100% for asystole and 99% for other non-shockable rhythms. In the presence of EMI, the specificity for some non-shockable rhythms (NSR, N) may be affected in some specific cases of a low signal-to-noise ratio and extreme frequencies, leading to a drop in the specificity with no more than 7% point. The specificity for asystole and the sensitivity for VF and rapid VT in the presence of any kind of 16.7, 50 or 60 Hz EMI simulated artifact were shown to reach the equivalence of sensitivity required for non-noisy signals. In conclusion, we proved that the shock advisory system working in a real AED operates accurately according to the AHA recommendations without artifacts and in the presence of EMI. The results may be affected for specificity in the case of a low signal-to-noise ratio or in some extreme frequency setting.

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Our study confirms the hypothesis that people with higher BMI, a growing section of the population, have lower ECG amplitudes. Therefore, the Sokolow-Lyon voltage criteria may underestimate the presence of LVH for subjects with higher BMI, which is not the case for the Cornell voltage. Our analysis suggests that computerized electrocardiography for the diagnosis of left ventricular hypertrophy based on Sokolow-Lyon voltages should incorporate the BMI factor.

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