Key result
A novel Dual-Slope based ECG peak detection method achieved a detection rate of 99.49% and a sensitivity of 99.74% when evaluated using the MIT/BIH Database.
A novel Dual-Slope based ECG peak detection method demonstrates high detection rate and sensitivity with low computational complexity, making it suitable for wearable devices.
Supports efficient wearable ECG monitoring; leaves open prospective clinical validation beyond benchmark databases.
This paper presents a new electrocardiogram (ECG) peak detection method based on Dual-Slope processing with low computational complexity, suitable for wearable devices. The method calculates the slopes on both sides of a data point, and only peak points can have a large response to this processing. The sliding window integral and low pass filter method are used to make the signal smoother and more suitable for peak detection. Two adaptive thresholds are used to justify the peak point. The algorithm, evaluated by using data in MIT/BIH Database, achieves a detection rate of 99.49%, a sensitivity of 99.74%.
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Haoran Li (2020) studied Electrocardiogram (ECG) peak detection. Dual-Slope based ECG peak detection method was evaluated on Detection rate and sensitivity. A novel Dual-Slope based ECG peak detection method achieved a detection rate of 99.49% and a sensitivity of 99.74% when evaluated using the MIT/BIH Database.
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