Heartbeat type classification method and device, and electrocardiogram equipment

Abstract

The invention discloses a heartbeat type classification method and device, and electrocardiogram equipment and belongs to the field of medical apparatuses. The method comprises steps that heartbeat waveform characteristic parameters are extracted from ECG signals, heartbeat and template heartbeat matching degree characteristic parameters are further extracted, analysis is carried out through a decision tree classifier, and the heartbeat type analysis result can be acquired through measurement. An extracted characteristic vector can be better present difference of the ECG signals, and disadvantages of utilizing only a waveform analytical method or a template analysis method are avoided. The invention further comprises the electrocardiogram equipment comprising the method. The method is advantaged in that the characteristic vector extraction algorithm is simple and easy for realization, the operation speed is fast, classification accuracy is high, and the method is suitable for a wearable electrocardiogram real-time monitoring automatic analysis diagnosis system.

Description

technical field [0001] The invention relates to the technical field of medical devices, in particular to a heartbeat type classification method, device and electrocardiograph. Background technique [0002] Cardiovascular disease remains the leading cause of death worldwide. The human electrocardiogram signal records the depolarization and repolarization process of heart cells, reflecting the generation and conduction process of cardiac electrical excitation. The evaluation provides an important basis. In modern medicine, the automatic detection and analysis of electrocardiogram (ECG) is of great significance for the analysis and diagnosis of cardiovascular diseases, and it is also the core component of many ECG monitoring equipment with automatic analysis and diagnosis functions. Therefore, automatic detection and analysis methods based on ECG have been extensively studied. [0003] There are certain differences in the existing classification methods of heartbeat types. T...

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Problems solved by technology

[0003] There are certain differences in the existing classification methods of heartbeat types. They are analyzed according to the characteristic waveforms in the electrocardiogram. The main parameters of the characteristic waveforms are: QRS complex wave width, waveform amplitude, waveform interval, waveform Morphological direction, etc. These characteristic waveform parameters are compared with the preset fixed judgment threshold, and the corresponding heartbeat type is judged acc

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