Onset Detection of Pulse-Shaped Bioelectrical Signals Using Linear State Space Models

Waldmann, Frédéric; Baeriswyl, Christof; Andonie, Raphael; Wildhaber, Reto A. (30 September 2022). Onset Detection of Pulse-Shaped Bioelectrical Signals Using Linear State Space Models In: BMT 2022: Abstracts of the 2022 Joint Annual Conference of the Austrian (ÖGBMT), German (VDE DGBMT) and Swiss (SSBE) Societies for Biomedical Engineering 67 (pp. 1-580). Berlin: Walter de Gruyter 10.1515/bmt-2022-2001

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Bioelectrical signals are often pulse-shaped with superimposed interference signals. In this context, accurate identification of features such as pulse onsets, peaks, ampli- tudes, 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.

Item Type:	Conference or Workshop Item (Abstract)
Division/Institute:	School of Engineering and Computer Science > Institute for Human Centered Engineering (HUCE) > HUCE / Laboratory for Microelectronics and Medical Devices
Name:	Waldmann, Frédéric; Baeriswyl, Christof; Andonie, Raphael and Wildhaber, Reto A.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher:	Walter de Gruyter
Language:	English
Submitter:	Christof Baeriswyl
Date Deposited:	22 Nov 2022 09:41
Last Modified:	22 Nov 2022 09:41
Publisher DOI:	10.1515/bmt-2022-2001
ARBOR DOI:	10.24451/arbor.18006
URI:	https://arbor.bfh.ch/id/eprint/18006