Atrial fibrillation detection method, classification model training method and terminal equipment

A detection method and technology for atrial fibrillation, applied in the field of medical data analysis, can solve the problems of poor performance and high false alarm rate of atrial fibrillation detection, and achieve the effect of accurate classification results of atrial fibrillation detection

Active Publication Date: 2017-11-24
陈一昕
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Problems solved by technology

[0004] In view of this, the embodiment of the present application provides an atrial fibrillation detection method, a classification model training method, and a terminal device to solve the technical problems of high false alarm rate and poor performance in atrial fibrillation detection in the prior art

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  • Atrial fibrillation detection method, classification model training method and terminal equipment
  • Atrial fibrillation detection method, classification model training method and terminal equipment
  • Atrial fibrillation detection method, classification model training method and terminal equipment

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Embodiment Construction

[0015] The present application is described below based on examples, but the present application is not limited only to these examples. In the following detailed description of the application, some specific details are set forth in detail. The present application can be fully understood by those skilled in the art without the description of these detailed parts. To avoid obscuring the essence of the present application, well-known methods, procedures, procedures, components and circuits have not been described in detail.

[0016] Additionally, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0017] Unless the context clearly requires, throughout the specification and claims, "comprises", "comprises" and similar words should be interpreted in an inclusive sense rather than an exclusive or exhaustive meaning; that is, "including but not limited to" meaning.

[0018] In...

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Abstract

The invention provides an atrial fibrillation detection method, a classification model training method and terminal equipment. The method comprises the steps of preprocessing an electrocardiogram signal, and acquiring a heart beat interval sequence with a preset length, which corresponds to each heart beat; and inputting the heart beat interval sequence to a transformation convolution neural network (TCNN) to obtain an atrial fibrillation detection classification result, wherein the transformation convolution neural network includes a transform layer, a local convolution layer and a global convolution layer. Atrial fibrillation detection is carried out on a real-time EGG (Electrocardiogram) signal by use of the TCNN obtained by training, the TCNN can be trained by use of the accumulated ECG and the atrial fibrillation detection classification result thereof so that an error of the TCNN is smaller and smaller and the atrial fibrillation detection classification result becomes more accurate.

Description

technical field [0001] The present application relates to the field of medical data analysis, in particular to a method for detecting atrial fibrillation, a method for training a classification model, and a terminal device. Background technique [0002] Atrial fibrillation (abbreviated as atrial fibrillation) is the most common sustained arrhythmia, often accompanied by symptoms such as palpitations, dizziness, chest discomfort, and shortness of breath. At present, AF detection methods are divided into methods based on R-R interval analysis and methods based on waveform recognition. Among them, the method based on waveform recognition is greatly affected by the results of waveform analysis, while the method based on R-R interval analysis is relatively stable and has better performance. [0003] Among the methods based on R-R interval analysis, the method with the best performance is the method based on sample entropy. After transforming the R-R interval, the sample entropy...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G06K9/00G06N3/04G06N3/08
CPCG06N3/084G06N3/045G06F2218/12
Inventor 陈一昕
Owner 陈一昕
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