Lukas Smital

TL;DR: This study focused on the reduction of broadband myopotentials (EMG) in ECG signals using the wavelet Wiener filtering with noise-free signal estimation and used the dyadic stationary wavelet transform (SWT) in the Wiener filter as well as in estimating the noise- free signal.

TL;DR: The paper introduces the results of a complex study, where various aspects of automatic classification of various heartbeat types have been addressed, and non-ischemic, ischemic and subsequent ventricular premature beats were classified in this combination for the first time.

TL;DR: The possibility of using the smartphone as a fast alternative to conventional and specialized devices for SpO2, HR, and BP estimation was statistically proven and the smartphone quantum efficiency did not have to be known.

TL;DR: An overview of objective algorithms for the assessment of both ECG signal quality after compression and compression efficiency and a combination of these methods are recommended: PSim SDNN, QS, SNR1, MSE, PRDN1, MAX, STDERR, and WEDD SWT.

TL;DR: A novel approach to estimate long-term ECG signal quality by calculation of continuous signal-to-noise ratio (SNR) curve is proposed and is found to be a robust, accurate and computationally efficient algorithm that will facilitate the subsequent tailored analysis of ECG signals recorded in free-living conditions.