In biomedical field, Equivalent Time sampling (ETS) techniques have never been applied to electrophysiological signal processing. ETS techniques allow to sample periodic and/or pseudo-periodic signals with a frequency much lower than the Nyquist limit frequency and therefore it may be applied to assess parameters of interest in the clinical field. In the present work, ETS algorithm has been used in the post-processing phase firstly to reconstruct different sine waveforms generated through an in-house mathematical software simulating physiological conditions and secondly to reconstruct a real ECG recording. The uncertainty of the ETS method for all the reconstructions carried on has been estimated by means of Monte Carlo Simulation (MCS). The results show that the reconstruction algorithm implemented is robust enough despite the influence of the heart rate and amplitude variability.
Fiori, G., Scorza, A., Conforto, S., Fuiano, F., Schmid, M., Sciuto, S.A. (2020). ECG Waveforms Reconstruction based on Equivalent Time Sampling. In IEEE Medical Measurements and Applications, MeMeA 2020 - Conference Proceedings (pp.1-6). Institute of Electrical and Electronics Engineers Inc. [10.1109/MeMeA49120.2020.9137260].
ECG Waveforms Reconstruction based on Equivalent Time Sampling
Fiori G.;Scorza A.;Conforto S.;Fuiano F.;Schmid M.;Sciuto S. A.
2020-01-01
Abstract
In biomedical field, Equivalent Time sampling (ETS) techniques have never been applied to electrophysiological signal processing. ETS techniques allow to sample periodic and/or pseudo-periodic signals with a frequency much lower than the Nyquist limit frequency and therefore it may be applied to assess parameters of interest in the clinical field. In the present work, ETS algorithm has been used in the post-processing phase firstly to reconstruct different sine waveforms generated through an in-house mathematical software simulating physiological conditions and secondly to reconstruct a real ECG recording. The uncertainty of the ETS method for all the reconstructions carried on has been estimated by means of Monte Carlo Simulation (MCS). The results show that the reconstruction algorithm implemented is robust enough despite the influence of the heart rate and amplitude variability.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
