Peer-Reviewed Journal Details
Mandatory Fields
Gutierrez-Rivas, R;Garcia, JJ;Marnane, WP;Hernandez, A
2015
October
IEEE Sensors Journal
Novel Real-Time Low-Complexity QRS Complex Detector Based on Adaptive Thresholding
Validated
WOS: 73 ()
Optional Fields
DETECTION ALGORITHM WAVELET TRANSFORM ECG MONITOR SYSTEM
15
6036
6043
Over the years, several QRS complex detection algorithms have been proposed with different features, but the remaining problem is their implementation in low-cost portable platforms for real-time applications, where hardware resources are limited, still providing the accuracy level required for medical applications. The proposed algorithm copes at the same time with both requirements: 1) accuracy and 2) low resource consumption. In this paper, a real-time QRS complex detector is proposed. This algorithm is based on a differentiation at the pre-processing stage combined with a dynamic threshold to detect R peaks. The thresholding stage is based on a finite-state machine, which modifies the threshold value according to the evolution of the signal and the previously detected peak. It has been evaluated on several databases, including the standard ones, thus resulting sensitivities and positive predictivities better than 99.3%. In order to analyze the computational complexity of the algorithm, it has been compared with the well-known Pan and Tompkins' algorithm. As a result, the proposed detector achieves a reduction in processing time of almost 50% by using only the 25% of hardware resources (memory, adders, and multipliers).
PISCATAWAY
1530-437X
10.1109/JSEN.2015.2450773
Grant Details