NDLI: Enabling R-peak detection in wearable ECG: Combining matched filtering and Hilbert transform

Content Provider	IEEE Xplore Digital Library
Author	Chanwimalueang, T. von Rosenberg, W. Mandic, D.P.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Electron. Eng, Imperial Coll. London, London, UK (Chanwimalueang, T.; von Rosenberg, W.; Mandic, D.P.)
Abstract	Precise detection of R-peaks is a prerequisite in real-world ECG applications - this is particularly critical for wearable ECG where sensors are typically low resolution and embedded. Such recorded ECG data are typically contaminated by noise, motion artefacts, unbalanced skin-electrode impedance and other physiological signals. These affect the quality of R-peak detection and can consequently lead to failure in the evaluation of physiological functions or a misinterpretation of the state of the body, such as in monitoring stress. While numerous methods for R-peak detection are available for stationary and comparably noise-free ECG, robust DSP software for wearable devices is still emerging. To this end, a new approach which combines matched filtering and Hilbert transform is proposed. The RR-intervals and cross-correlation are used in conjunction to not only automatically locate the R-peaks but also to display the candidate ambiguous peaks via an interactive graphical user interface. The performance of the proposed approach is compared to the well-known Pan-Tompkins algorithm and is evaluated for two types of ECG databases: standard stationary data and low-SNR ECG data obtained from wearable ECG. The proposed method results in a distinctly higher positive predictivity and leads to more satisfying overall outcomes, especially for the critical call of low-SNR data.
Starting Page	134
Ending Page	138
File Size	170687
Page Count	5
File Format	PDF
ISSN	21653577
e-ISBN	9781479980581
DOI	10.1109/ICDSP.2015.7251845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-21
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrocardiography Transforms Databases Biomedical monitoring Software Heart rate variability wearable devices R-peak detection RR-interval ECG QRS detection matched filtering Hilbert transform
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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