Why the study?
Does an efficient R-peak detection algorithm perform comparably to traditional methods for real-time analysis on portable devices?
Does an efficient R-peak detection algorithm perform comparably to traditional methods for real-time analysis on portable devices?
A new efficient R-peak detection algorithm enables real-time ECG processing on low-cost portable devices with performance comparable to traditional clinical methods.
Answers are grounded in this paper and cite their sources.
May support portable ECG development; leaves open clinical validation before practice adoption.
Detection of R-peaks in an electrocardiogram (ECG) acquisition is the primary goal of any algorithm for the automatic processing of ECG signals. Several methods have been proposed in the past to accomplish this task, but usually they are designed for the use in clinical situations, where strict real-time requirements are not always needed and availability of devices with high computational resources is not a problem. The recent and broad success of personal and portable devices for health monitoring has opened a new scenario, in which new algorithms need to be developed in order to satisfy constraints due to limited computational resources and the need of having embedded and real-time data processing. This work describes an efficient algorithm for the R-peak detection, designed for low-cost and low-performing portable devices. Performance of the proposed approach, evaluated with a set of well-known ECG waveform, is comparable with traditional methods found in literature. Finally, the successful implementation of the algorithm in a smartphone-based low-cost ECG acquisition system has validated the feasibility of the proposed approach.
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Crema et al. (2016) studied this question.
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