Multi-class arrhythmia detection method based on lead attention mechanism
A technology of arrhythmia and detection method, which is applied in the field of medical signal processing, can solve the problem of ignoring the characteristics of 12-lead ECG signals, etc., and achieve the effect of improving the detection performance of arrhythmia and the detection performance
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[0057] In this embodiment, a multi-type arrhythmia detection method based on the lead attention mechanism is named LTA-CNN, such as figure 1 As shown, it includes the following steps:
[0058] Step 1. Obtain the original ECG signal and its corresponding label, down-sample the original ECG signal to obtain the sampled ECG signal; perform clipping or mean value filling processing on the sampled ECG signal to obtain the pre-processed ECG signal;
[0059] Step 1.1. Obtain the original ECG signal and its corresponding label required for the experiment from the public data of the China Physiological Signal Challenge (CPSC) 2018. The public data of CPSC2018 provides 6877 12-lead ECG records with a time length ranging from 6 seconds to 60 seconds. Records were collected from 11 hospitals with a sampling rate of 500 Hz. The ECG records contained nine heart rhythm types, eight arrhythmias and normal heart rhythms, as shown in Table 1.
[0060] Table 1: Configuration of the dataset
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