RT Journal Article
A1 M. Sabarimalai Manikandan
AD School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, Odisha-751013, India
A1 Barathram Ramkumar
AD School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, Odisha-751013, India

PB iet
T1 Straightforward and robust QRS detection algorithm for wearable cardiac monitor
JN Healthcare Technology Letters
VO 1
IS 1
SP 40
OP 44
AB This Letter presents a fairly straightforward and robust QRS detector for wearable cardiac monitoring applications. The first stage of the QRS detector contains a powerful ℓ1-sparsity filter with overcomplete hybrid dictionaries for emphasising the QRS complexes and suppressing the baseline drifts, powerline interference and large P/T waves. The second stage is a simple peak-finding logic based on the Gaussian derivative filter for automatically finding locations of R-peaks in the ECG signal. Experiments on the standard MIT-BIH arrythmia database show that the method achieves an average sensitivity of 99.91% and positive predictivity of 99.92%. Unlike existing methods, the proposed method improves detection performance under small-QRS, wide-QRS complexes and noisy conditions without using the searchback algorithms.
K1 powerline interference
K1 wide-QRS complexes
K1 wearable cardiac monitoring
K1 ℓ1-sparsity filter
K1 standard MIT-BIH arrythmia database
K1 noisy conditions
K1 QRS detection algorithm
K1 R-peaks
K1 Gaussian derivative filter
K1 baseline drifts
K1 ECG signal
DO https://doi.org/10.1049/htl.2013.0019
UL https://digital-library.theiet.org/;jsessionid=3s8tkmi8r99c2.x-iet-live-01content/journals/10.1049/htl.2013.0019
LA English
SN
YR 2014
OL EN