Single-guided heart stick data intelligent diagnosis cloud calculation system and processing method thereof

Abstract

The invention discloses a single-guided heart stick data intelligent diagnosis cloud calculation system and a processing method thereof. The system comprises a client acquisition module, a storage service module, a message queue service module and a calculation service module, wherein the client acquisition module is used for acquiring long-term dynamic electrocardiogram (EEG) data of a single-guided heart stick, uploading the data to the storage service module and downloading required data from the storage service module, the storage service module is used for storing the long-term dynamic ECG data and the ECG analysis report, the message queue service module is used for realizing message transmission and function decoupling, the calculation service module is used for providing hardware resources required for calculation, an ECG scatter plot is drawn based on the long-term dynamic electrocardiogram data of the single-guided heart stick, an AI model is utilized to carry out artificialintelligence diagnosis of the ECG scatter plot, the classification result of the ECG scatter plot is calculated, and the ECG analysis report is formed. The system is advantaged in that on the basis ofstorage service and calculation service of the cloud service architecture, the analysis speed of the dynamic ECG and diagnosis accuracy are effectively improved.

Description

technical field [0001] The invention relates to the technical field of medical electronic equipment intelligent services, in particular to a cloud computing system for intelligent diagnosis of single-guided heart-tie data and a processing method thereof. Background technique [0002] Cardiovascular disease is a major threat to human health. According to authoritative surveys, the number of people who die from cardiovascular disease accounts for about one-third of the total number of human deaths every year. [0003] For arrhythmia, a common clinical manifestation of cardiovascular disease, the value of long-term ambulatory electrocardiogram is higher, because some arrhythmias are not easy to collect in 12-lead static ECG examination, and are more likely to be detected in long-term or all-weather detected in dynamic scenes. [0004] Long-term ECG data requires a large amount of memory to store due to the large data, while general devices such as client devices and single-le...

AI Technical Summary

Problems solved by technology

[0004] Long-term ECG data requires a large amount of memory to store due to the large data, and general devices such as clients and single-lead heart stickers cannot meet the storage of large amounts of data due to memory limitations

At the same time, in order to ensure the timeliness of the diagnostic results, the AI ​​analysis of long-term ECG data needs to obtain the analysis results within a certain period of time. Therefore, higher requirements are placed on computer resources, such as CPU and GPU. The client is subject to many restrictions on hardware configuration, and it is difficult to meet the requirements of AI algorithm analysis

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