Key result
An adaptive threshold QRS detection algorithm achieved over 99% correct detection of QRS complexes when tested on 20 series of ECG data from the AHA arrhythmia database.
Why the study?
Does an adaptive threshold algorithm accurately detect QRS complexes in ambulatory ECG signals?
Does an adaptive threshold algorithm accurately detect QRS complexes in ambulatory ECG signals?
An adaptive threshold algorithm achieved over 99% correct detection of QRS complexes in ambulatory ECG signals from the AHA arrhythmia database.
Supports adaptive QRS detection in database ECGs; leaves open prospective ambulatory validation before clinical use.
The authors have developed an algorithm for detection of QRS complexes of ambulatory electrocardiogram (ECG) signals. The threshold, which is obtained from a distribution function of the amplitude of the filtered ECG signal, changes with time, adapting to changes in the QRS morphology, levels of noise, and artifacts. The threshold extracts the period which include the QRS complex, and then the QRS complex is detected during this period. By using 20 series of single-channel ECG data selected from the AHA arrhythmia database, the usefulness of this algorithm was investigated, counting both numbers of false positive (FP) and false negative (FN) QRS complexes. Correct detection of over 99% was achieved.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Akazawa et al. (2002) studied Ambulatory ECG signals (n=20). Adaptive threshold QRS detection algorithm was evaluated on Correct detection of QRS complexes. An adaptive threshold QRS detection algorithm achieved over 99% correct detection of QRS complexes when tested on 20 series of ECG data from the AHA arrhythmia database.
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