A new QRS detector stress test combining temporal jitter and F-score (JF) reveals significant performance differences amongst popular detectors

QRS detection within an electrocardiogram (ECG) is the basis of virtually any further processing and any error caused by this detection will propagate to further processing stages. However, standard benchmarking procedures of QRS detectors are seriously flawed because they report almost always close...

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Bibliographic Details
Published inPloS one Vol. 19; no. 11; p. e0309739
Main Authors Porr, Bernd, Macfarlane, Peter W.
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 11.11.2024
Public Library of Science (PLoS)
Subjects
Accuracy
Algorithms
Analysis
Annotations
Cardiac arrhythmia
Cardiac stress tests
Databases, Factual
Detectors
EKG
Electrocardiogram
Electrocardiography
Electrocardiography - instrumentation
Electrocardiography - methods
Engineering and Technology
Error detection
Health aspects
Heart beat
Heart rate
Humans
Medicine and Health Sciences
Noise measurement
People and Places
Physical Sciences
Research and Analysis Methods
Sensors
Signal Processing, Computer-Assisted
Signal-To-Noise Ratio
Stress (Physiology)
Vibration
United Kingdom
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ISSN1932-6203
1932-6203
DOI10.1371/journal.pone.0309739

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Summary:QRS detection within an electrocardiogram (ECG) is the basis of virtually any further processing and any error caused by this detection will propagate to further processing stages. However, standard benchmarking procedures of QRS detectors are seriously flawed because they report almost always close to 100% accuracy for any QRS detection algorithm. This is due to the use of large temporal error margins and noise-free ECG databases which grossly overestimate their performance. The use of a large fixed error margin masks temporal jitter between detection and ground truth measurements. Here, we present a new performance measure (JF) which combines temporal jitter with the F-score, and also an ECG database with decreasing levels of signal to noise ratios based on noise generated from different tasks. Our new performance measure JF fully encompasses all the types of errors that can occur, equally weights them and provides a percentage value which allows direct comparison between QRS detection algorithms. In combination with the new noisy ECG database, the JF performance measure now varies between 50% and 100% for different detectors and signal to noise conditions thereby making it possible to find the best detector for an application.
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Competing Interests: B.P. is CEO of Glasgow Neuro LTD which manufactures the Attys DAQ board. He has received a salary from Glasgow Neuro LTD which, however, did not provide any funding for this study. B.P. was involved in the design, data analysis, decision to publish, and preparation of the manuscript. However, this study is not about comparing different ECG measurement devices. The outcome of this study will be identical with other commercial data acquisition devices with identical specifications and the Attys does not alter the originally measured data in any way and thus does not introduce any bias. This does not alter our adherence to PLOS ONE policies on sharing data and materials. All data is available publicly and in its unprocessed format as measured by the Attys. There are no patents, products in development, or marketed products associated with this research to declare.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0309739