Conference contribution
(Conference Contribution)


Filter and Processing Method to Improve R-Peak Detection for ECG Data with Motion Artefacts from Wearable Systems


Publication Details
Author(s): Lang N, Brischwein M, Haßlmeyer E, Tantinger D, Feilner S, Heinrich A, Leutheuser H, Gradl S, Weigand C, Eskofier B, Struck M
Publisher: IEEE Computer Society
Publication year: 2015
Conference Proceedings Title: Computing in Cardiology 2015
Pages range: 917-920
ISBN: 9781509006854

Event details
Event: Computing in Cardiology
Event location: Nice, France
Start date of the event: 06/09/2015
End date of the event: 09/09/2015

Abstract
The electrocardiogram (ECG) is one of the most reliable information sources for assessing cardiovascular health and training success. Since the early 1990s, the heart rate variability (HRV), namely the variation from beat to beat, has become the focus of investigations as it provides insight into the complex interplay of body circulation and the influence of the autonomic nervous system on heartbeats. However, HRV parameters during physical activity are poorly understood, mostly due to the challenging signal processing in the presence of motion artefacts. To derive HRV parameters in time (heart rate (HR)) and frequency domains (high frequency (HF), low frequency (LF)), it is crucial to reliably detect the exact position of the R-peaks. We introduce a full algorithm chain where a sophisticated filtering technique is combined with an enhanced R-peak detection that can cope with motion artefacts in ECG data originating from physical activity.


How to cite
APA: Lang, N., Brischwein, M., Haßlmeyer, E., Tantinger, D., Feilner, S., Heinrich, A.,... Struck, M. (2015). Filter and Processing Method to Improve R-Peak Detection for ECG Data with Motion Artefacts from Wearable Systems. In Computing in Cardiology 2015 (pp. 917-920). Nice, France: IEEE Computer Society.

MLA: Lang, Nadine, et al. "Filter and Processing Method to Improve R-Peak Detection for ECG Data with Motion Artefacts from Wearable Systems." Proceedings of the Computing in Cardiology, Nice, France IEEE Computer Society, 2015. 917-920.

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