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Wednesday, November 15 • 11:20 - 11:40
A Review on Digital Signal Processing Approaches in ECG R-peak Detection

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Extracting as much information as possible from electrocardiography (ECG) has been a target for researchers for decades. In this work, three DSP based R-peak detection methods are reviewed, including the Pan-Tompkins algorithm, and methods based on the Hilbert transform and wavelet transform. Those algorithms are applied to the publicly available MIT/BIH arrhythmia database and a database collected by the authors. While all three approaches derived the same results when applied to the authors' database, they showed slightly different performance when applied to the MIT/BIH arrhythmia database: Hilbert transform based method showed very good performance with 99.87% of accuracy, higher than those from wavelet transform based approach (99.55%) and Pan-Tompkins algorithm (99.34%). However, Pan-Tompkins algorithm is the most computationally efficient (approximately 4.3 times faster than wavelet transform method, and 42.5 times faster than Hilbert transform method).

Wednesday November 15, 2017 11:20 - 11:40
Conception Bay North 180 Portugal Cove Road, St. John's, NL, Canada

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