Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Niederhauser, Thomas; Wyss-Balmer, T; Häberlin, Andreas; Marisa, Thanks; Wildhaber, Reto; Götte, Josef; Jacomet, M; Vogel, Rolf (2015). Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography. IEEE transactions on biomedical engineering, 62(6), pp. 1576-1584. Institute of Electrical and Electronics Engineers IEEE 10.1109/TBME.2015.2395456

[img] Text
07035014.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (1MB) | Request a copy

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Cardiovascular Disorders (DHGE) > Clinic of Cardiology
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Cardiovascular Engineering (CVE)

UniBE Contributor:

Niederhauser, Thomas; Häberlin, Andreas; Marisa, Thanks; Wildhaber, Reto; Götte, Josef and Vogel, Rolf

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

0018-9294

Publisher:

Institute of Electrical and Electronics Engineers IEEE

Language:

English

Submitter:

Dr. Andreas Häberlin

Date Deposited:

04 Jun 2015 16:16

Last Modified:

10 Jun 2016 08:06

Publisher DOI:

10.1109/TBME.2015.2395456

PubMed ID:

25675449

BORIS DOI:

10.7892/boris.69012

URI:

https://boris.unibe.ch/id/eprint/69012

Actions (login required)

Edit item Edit item
Provide Feedback