(De Gruyter, 02.09.2022) Waldmann, Frédéric; Baeriswyl, Christof; Andonie, Raphael; Wildhaber, Reto [in: Current Directions in Biomedical Engineering]
Bioelectrical signals are often pulse-shaped with superimposed interference signals. In this context, accurate identification of features such as pulse onsets, peaks, amplitudes, and duration is a frequent problem. In this paper, we present a versatile method of rather low computational complexity to robustly identify such features in real-world signals. For that, we take use of two straight-line models fit to the observations by minimizing a quadratic cost term, and then identify desired features by tweaked likelihood measures. To demonstrate the idea and facilitate access to the method, we provide examples from the field of cardiology.
