Key result
A novel R-peak detection algorithm using triangle template matching and a moving average filter demonstrated good accuracy and low resource complexity across eight public ECG databases.
Why the study?
Wearable ECG devices require an R-peak detection algorithm with robustness to noise, low latency processing, low resource complexity, and automatic parameter tuning.
A novel, low-resource R-peak detection algorithm demonstrates good accuracy on public ECG databases, showing potential for use in wearable devices.
A novel R-peak detection algorithm suitable for wearable electrocardiogram (ECG) devices is proposed with four objectives: robustness to noise, low latency processing, low resource complexity, and automatic tuning of parameters. The approach is a two-pronged algorithm comprising (1) triangle template matching to accentuate the slope information of the R-peaks and (2) a single moving average filter to define a dynamic threshold for peak detection. The proposed algorithm was validated on eight ECG public databases. The obtained results not only presented good accuracy, but also low resource complexity, all of which show great potential for detection R-peaks in ECG signals collected from wearable devices.
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Nguyen et al. (2019) studied Electrocardiogram (ECG) R-peak detection. R-peak detection algorithm based on triangle template matching and moving average filter was evaluated on Accuracy and resource complexity. A novel R-peak detection algorithm using triangle template matching and a moving average filter demonstrated good accuracy and low resource complexity across eight public ECG databases.
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