Table 2.

Ten selected QRS detection algorithms.

Methods	Filtering	Extracting features	Setting threshold	Postprocessing
Pan–Tompkins algorithm [15]	5–15 Hz band-pass filter	Derivative; square; integrate	Two sets of adaptive thresholds	Searching back; T wave judging
Hamilton-mean algorithm [11]
Hamilton-median algorithm [11]
RS slope algorithm [21–23]	Median filter	Derivative; detecting negative slope	10 groups of duration empirical thresholds; one fixed amplitude threshold	200 ms refractory blanking technology
Sixth power algorithm [24]	Two-stage median filter	Sixth power	One adaptive threshold	Determining end point K
Finite state machine (FSM) algorithm [25]	/	Derivative; integrate; square	Three thresholding stages	/
U3 transform algorithm (U3) [26]	8–30 Hz band-pass filter	U3 transform	Two fixed thresholds	Searching back; 270 ms refractory blanking technology
Difference operation algorithm (DOM) [2, 27]	8–30 Hz band-pass filter	Derivative; detecting positive extreme points	Positive threshold; negative threshold	Optimizing; matching filtered signal
“jqrs” algorithm [28–30]	Sombrero hat-like low-pass filter	Integrate	One fixed threshold	Searching back; 200 ms refractory blanking technology
Optimized knowledge-based algorithm (OKB) [1]	8–20 Hz band-pass filter	Squaring; integration	Two dynamic thresholds	Determining the maxima of each block as R peak