Key result
The proposed dual-slope QRS detection algorithm achieved a 99.38% detection rate on the MIT/BIH arrhythmia database and had a 12.48 times faster runtime compared to a recent dual-slope method.
Why the study?
Does the proposed dual-slope QRS detection algorithm improve detection rate and runtime compared to existing methods in ECG signals?
Does the proposed dual-slope QRS detection algorithm improve detection rate and runtime compared to existing methods in ECG signals?
The proposed dual-slope QRS detection algorithm offers high accuracy (99.38%) and significantly faster runtime (12.48x) for wearable ECG applications.
This paper presents a computationally efficient QRS detection algorithm for wearable electrocardiogram (ECG) applications based on dual-slope analysis. In general, ECG signals of arrhythmias are pseudo-periodic and contaminated with noises like the patient's contraction muscles, respiration, 60 Hz interference and other types which impede correct QRS detection. To resolve this problem, in this paper, a technique is presented which is based on two slopes on both sides of a peak in ECG signal. Based on these slopes, a variable measuring steepness is developed and R peaks are detected. The algorithm was evaluated against MIT/BIH arrhythmia database and achieved 99.38% detection rate. This method was compared with one of the recently developed dual-slope based QRS detection methods. The results showed that the proposed method has 12.48 times faster runtime than the old method.
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Arefin et al. (2014) studied Arrhythmias. Dual-slope based QRS detection algorithm vs. Recently developed dual-slope based QRS detection method was evaluated on QRS detection rate and runtime (12.48 times faster runtime). The proposed dual-slope QRS detection algorithm achieved a 99.38% detection rate on the MIT/BIH arrhythmia database and had a 12.48 times faster runtime compared to a recent dual-slope method.
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