Auflistung nach Autor:in "Marisa, Thanks"

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A baseline wander tracking system for artifact rejection in long-term electrocardiography
(IEEE, 2016) Niederhauser, Thomas; Marisa, Thanks; Kohler, Lukas; Haeberlin, Andreas; Wildhaber, Reto; Abächerli, Roger; Goette, Josef; Jacomet, Marcel; Vogel, Rolf
Long-term electrocardiogram (ECG) signals might suffer from relevant baseline disturbances during physical activity. Motion artifacts in particular are more pronounced with dry surface or esophageal electrodes which are dedicated to prolonged ECG recording. In this paper we present a method called baseline wander tracking (BWT) that tracks and rejects strong baseline disturbances and avoids concurrent saturation of the analog front-end. The proposed algorithm shifts the baseline level of the ECG signal to the middle of the dynamic input range. Due to the fast offset shifts, that produce much steeper signal portions than the normal ECG waves, the true ECG signal can be reconstructed offline and filtered using computationally intensive algorithms. Based on Monte Carlo simulations we observed reconstruction errors mainly caused by the non-linearity inaccuracies of the DAC. However, the signal to error ratio of the BWT is higher compared to an analog front-end featuring a dynamic input ranges above 15 mV if a synthetic ECG signal was used. The BWT is additionally able to suppress (electrode) offset potentials without introducing long transients. Due to its structural simplicity, memory efficiency and the DC coupling capability, the BWT is dedicated to high integration required in long-term and low-power ECG recording systems.
01A - Beitrag in wissenschaftlicher Zeitschrift
Graphics-processor-unit-based parallelization of optimized baseline wander filtering algorithms for long-term electrocardiography
(IEEE, 2015) Niederhauser, Thomas; Wyss-Balmer, Thomas; Haeberlin, Andreas; Marisa, Thanks; Wildhaber, Reto; Goette, Josef; Jacomet, Marcel; Vogel, Rolf
Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here, we present a graphics processor unit (GPU)-based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to autoregressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and four times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a seven-day high-resolution ECG is computed within less than 3 s. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.
01A - Beitrag in wissenschaftlicher Zeitschrift
Markers for silent atrial fibrillation in esophageal long-term electrocardiography
(Elsevier, 2016) Haeberlin, Andreas; Lacheta, Lucca; Niederhauser, Thomas; Marisa, Thanks; Wildhaber, Reto; Goette, Josef; Jacomet, Marcel; Seiler, Jens; Fuhrer, Juerg; Roten, Laurent; Tanner, Hildegard; Vogel, Rolf
Purpose Paroxysmal atrial fibrillation (PAF) often remains undiagnosed. Long-term surface ECG is used for screening, but has limitations. Esophageal ECG (eECG) allows recording high quality atrial signals, which were used to identify markers for PAF.
01A - Beitrag in wissenschaftlicher Zeitschrift