The invention belongs to the technical field of
medical information processing, and discloses a single-lead ECG
arrhythmia detection and classification method and
system based on a residual network, and the method comprises the steps: carrying out the segmentation of an original
ECG signal: taking one second as a window length, and carrying out the segmentation of the original
ECG signal;
processing and the signals by using a residual error network: inputting the segmented data into the network, and the processed
network output result being the identification result of the corresponding
ECG signal. According to the method, the original electrocardiosignal does not need to be subjected to sub-shooting
processing, and any alignment is not needed. Classification and identification of
normal heart beat, left bundle
branch conduction blocking, right bundle
branch conduction blocking, atrial premature beat, abnormal atrial premature beat, boundary premature beat, ventricular premature beat,supraventricular premature beat, ventricular fusion
heartbeat, atrial escape beat, boundary escape beat, ventricular escape beat, pacing
heart beat and pacing fusion
heartbeat can be realized. Test comprehensive accuracy on MIT-BIH arrhythmia
database reaches 96% or above.