The invention requests to protect a real-time electrocardiogram classification method based on
random projection, and aims to solve the problems of
data acquisition and computation and
power consumption transmission with which a remote electrocardiogram
monitoring system faces and the problem that electrocardiogram cannot be classified in real time. Five types of
heartbeat are classified into normal pulsation, atrial premature beat, ventricular premature beat, left bundle
branch block and right bundle
branch block. The method comprises the following steps: (1) data preprocessing; (2) characteristic extraction: on the basis of a
compressed sensing principle, compressing data, calculating an
RR interval and an RR weight, and splicing characteristic vectors to form second characteristics; (3) classification: dividing secondary characteristic data into training data and
test data, wherein the training data and the
test data are independently used for modeling
ant testing; and (4) decision classification: carrying out multiple-lead
classification result data fusion. The step of data preprocessing comprises the following specific steps: 1) filtering an electrocardiosignal, and removing interference; 2) carrying out waveform detection and segmentation; 3) carrying out data
standardization. The electrocardiogram
data classification method provided by the invention is accurate in a
classification result, and improves
data processing capability.