The invention discloses an R wave
rapid detection algorithm adaptive to electrocardiogram waveform
pathological change. The method, by summarizing the different characteristics of various
pathological electrocardiograms such as arrhythmia, reverse wave, W wave, tall peaked
P wave, tall peaked
T wave and the like on an electrocardiogram
signal first-order derivative and a first-order derivative square
signal, can overcome the limitation of a conventional difference threshold
algorithm on setting a plurality of thresholds and avoid the influence on self-adaption threshold detection due to relatively
high heart rate variability among different patients through such strategies as low-threshold return-to-zero treatment, R wave classification detection as well as threshold judgment and updating for a non-classical R waveform and the like. According to the method, the
algorithm is simple and easy to implement, and simultaneously the algorithm is capable of achieving rapid and accurate R
wave detection on the various
pathological electrocardiograms; and the algorithm is especially suitable for real-time QRS
wave detection on electrocardiogram signals in mobile portable equipment. The algorithm disclosed by the invention, inspected by virtue of an MIT-BIH
database, is 99.71% in sensitivity and is 99.73% in positive
predictive value.