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Electrocardiogram abnormality detection method, terminal and server

A technology for electrical anomaly detection and anomaly detection, which is used in sensors, diagnostic recording/measurement, medical science, etc. It can solve the problems of time-consuming and large computing power, and achieve the effect of solving the problem of time-consuming computing and improving the accuracy of analysis.

Pending Publication Date: 2020-07-17
LENOVO (BEIJING) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Embodiments of the present invention creatively provide a method for abnormal ECG detection, a terminal, and a server in order to solve the problem of large computing power and serious time-consuming detection of abnormal ECG

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  • Electrocardiogram abnormality detection method, terminal and server
  • Electrocardiogram abnormality detection method, terminal and server
  • Electrocardiogram abnormality detection method, terminal and server

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Embodiment Construction

[0026] The principle and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present invention, rather than to limit the scope of the present invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0027] The technical solutions of the present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0028] figure 1 It shows a network architecture diagram of an application example of the present invention to realize ECG abnormality detection; figure 2 It shows a schematic diagram of the process interaction of the embodiment of the present invention to realize the abnormal detection of electroc...

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PUM

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Abstract

The invention discloses an electrocardiogram abnormality detection method, a terminal and a server. The method comprises the following steps: firstly, acquiring electrocardiogram data by using a terminal (namely, an equipment end), and analyzing the electrocardiogram data one frame by one frame to obtain electrocardiogram waveform characteristics; sequentially sending the electrocardiogram data and the electrocardiogram waveform characteristics to a server (namely, a cloud end) to indicate the server to carry out off-line electrocardiogram abnormality detection by using the electrocardiogram data and the electrocardiogram waveform characteristics to obtain an off-line electrocardiogram abnormality detection result; and meanwhile, carrying out real-time electrocardiogram abnormality detection by the terminal based on the electrocardiogram data, sending the real-time electrocardiogram abnormality detection result to the server, and further carrying out electrocardiogram abnormality diagnosis by the server according to the real-time electrocardiogram abnormality detection result of the terminal and the off-line electrocardiogram abnormality detection result of the server so as to obtain an electrocardiogram abnormality diagnosis result.

Description

technical field [0001] The invention relates to electrocardiographic detection technology, in particular to a method for detecting abnormal electrocardiogram, a terminal and a server. Background technique [0002] At present, in order to analyze the ECG data collected by wearable dynamic ECG devices, provide doctors with more accurate analysis information, and reduce workload, relevant ECG algorithms are getting more and more attention. On the device side or mobile handheld devices, due to the limitation of computing power and resources, although the real-time ECG algorithm can analyze in time, the accuracy of detection and identification of abnormal ECG signals is very low; and the offline ECG algorithm after data collection With the help of machine learning, deep learning and other methods, the accuracy of ECG abnormality detection and recognition has been improved, but the calculation takes a long time, and the real-time response does not meet the needs of doctors. Cont...

Claims

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Application Information

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IPC IPC(8): A61B5/0402A61B5/04A61B5/00
CPCA61B5/72A61B5/7235A61B5/746A61B5/316A61B5/318
Inventor 黄茂林盖彦荣徐平吕晓
Owner LENOVO (BEIJING) CO LTD
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