Performance Analysis of Ten Common QRS Detectors on Different ECG Application Cases
Joint Authors
Zhang, Yatao
Li, JianQing
Liu, Feifei
Jiang, Xinge
Zhang, Zhimin
Liu, Chengyu
Wei, Shoushui
Source
Journal of Healthcare Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-08
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A systematical evaluation work was performed on ten widely used and high-efficient QRS detection algorithms in this study, aiming at verifying their performances and usefulness in different application situations.
Four experiments were carried on six internationally recognized databases.
Firstly, in the test of high-quality ECG database versus low-quality ECG database, for high signal quality database, all ten QRS detection algorithms had very high detection accuracy (F1 >99%), whereas the F1 results decrease significantly for the poor signal-quality ECG signals (all <80%).
Secondly, in the test of normal ECG database versus arrhythmic ECG database, all ten QRS detection algorithms had good F1 results for these two databases (all >95% except RS slope algorithm with 94.24% on normal ECG database and 94.44% on arrhythmia database).
Thirdly, for the paced rhythm ECG database, all ten algorithms were immune to the paced beats (>94%) except the RS slope method, which only output a low F1 result of 78.99%.
At last, the detection accuracies had obvious decreases when dealing with the dynamic telehealth ECG signals (all <80%) except OKB algorithm with 80.43%.
Furthermore, the time costs from analyzing a 10 s ECG segment were given as the quantitative index of the computational complexity.
All ten algorithms had high numerical efficiency (all <4 ms) except RS slope (94.07 ms) and sixth power algorithms (8.25 ms).
And OKB algorithm had the highest numerical efficiency (1.54 ms).
American Psychological Association (APA)
Liu, Feifei& Liu, Chengyu& Jiang, Xinge& Zhang, Zhimin& Zhang, Yatao& Li, JianQing…[et al.]. 2018. Performance Analysis of Ten Common QRS Detectors on Different ECG Application Cases. Journal of Healthcare Engineering،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1191328
Modern Language Association (MLA)
Liu, Feifei…[et al.]. Performance Analysis of Ten Common QRS Detectors on Different ECG Application Cases. Journal of Healthcare Engineering No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1191328
American Medical Association (AMA)
Liu, Feifei& Liu, Chengyu& Jiang, Xinge& Zhang, Zhimin& Zhang, Yatao& Li, JianQing…[et al.]. Performance Analysis of Ten Common QRS Detectors on Different ECG Application Cases. Journal of Healthcare Engineering. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1191328
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191328