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Sleep apnea hypopnea syndrome evaluation method and device based on target detection framework

A sleep apnea and target detection technology, applied in the computer field, can solve the problems of uncertain length of SAHS fragments, inability to meet the precise positioning of fragments, destroying the integrity of real fragments, etc., and achieve the effect of accurate positioning and accurate recognition

Active Publication Date: 2022-02-01
江西脑调控技术发展有限公司
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

[0003] Traditional SAHS evaluation methods often use template matching to find the salient features of SAHS fragments and calibrate the fragments that meet the standards; however, this type of evaluation algorithm depends on specific tasks, is highly customizable, and is very difficult to transfer between different signal fragment recognition tasks Big
The classification algorithm based on feature engineering or feature learning can be applied to different segment recognition tasks. This type of algorithm obtains a feature set through manual feature extraction or feature learning, and then determines whether the input segment belongs to a specific signal segment through classification; but based on A key problem in the classification algorithm is that it can only determine the type of input fragments, and cannot solve the problem of positioning specific fragments; and because the length of SAHS fragments is uncertain, the sliding window algorithm based on a single fixed-length time window It will also destroy the integrity of the real fragment and cannot meet the needs of precise positioning of the fragment

Method used

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  • Sleep apnea hypopnea syndrome evaluation method and device based on target detection framework
  • Sleep apnea hypopnea syndrome evaluation method and device based on target detection framework
  • Sleep apnea hypopnea syndrome evaluation method and device based on target detection framework

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Embodiment 1

[0045] An embodiment of the present invention provides a method for evaluating sleep apnea hypopnea syndrome based on a target detection framework, including:

[0046] S1: Collect raw sleep physiological index data;

[0047] S2: Preprocessing the collected raw sleep physiological index data, and labeling SAHS fragments;

[0048] S3: Construct the SAHS target detection framework. The SAHS target detection framework includes a backbone network module for fusing features, a region candidate module for generating detection candidate frames, and a sequence modeling module for classifying candidate sequences. The candidate frame can get the start and end points of each candidate SAHS segment;

[0049] S4: Obtain training data from the preprocessed and labeled data, and use the training data to train the SAHS target detection framework;

[0050] S5: Use the trained SAHS target detection framework to detect the data to be recognized.

[0051] The invention proposes a sleep apnea hypo...

Embodiment 2

[0107] Based on the same inventive concept, this embodiment provides a device for evaluating sleep apnea hypopnea syndrome based on a target detection framework, including:

[0108] A data collection module, used to collect raw sleep physiological index data;

[0109] The preprocessing module is used to preprocess the collected raw sleep physiological index data and mark the SAHS segment;

[0110] Target detection framework building block, used to build SAHS target detection framework, SAHS target detection framework includes backbone network module for fusing features, region candidate module for generating detection candidate boxes, and sequence modeling for classifying candidate sequences module;

[0111] The training module is used to obtain training data from the preprocessed and marked data, and use the training data to train the SAHS target detection framework;

[0112] The detection module is used to detect the data to be recognized by using the trained SAHS target d...

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Abstract

The invention provides a sleep apnea hypopnea syndrome (SAHS) evaluation method and device based on a target detection framework, wherein mouth-nose airflow and chest pressure data in sleep monitoring data are selected as data basis of SAHS evaluation, a target detection model fusing the mouth-nose airflow and the chest pressure data is designed, and the model comprises three main parts: respectively processing mouth-nose airflow and chest pressure data in a time sequence form, and fusing extracted features; carrying out adaptive regression on the basis of a region proposal network (RPN) to generate a candidate frame for SAHS fragment detection; and generating scale-invariant features based on the candidate segments and classifying the scale-invariant features. According to the invention, model training adopts an alternate training mode, and a RPN network and a classification network are trained respectively; and a focal loss function is used to alleviate a deviation problem possibly caused by model training under an unbalanced sample.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method and device for evaluating sleep apnea hypopnea syndrome based on a target detection framework. Background technique [0002] Sleep apnea-hypopnea syndrome (SAHS) refers to the clinical syndrome of recurrent apnea and / or hypopnea, hypercapnia, and sleep interruption caused by various reasons in the sleep state, resulting in a series of pathophysiological changes in the body. It is a typical symptom of sleep disorders. The sleep apnea-hypopnea syndrome assessment method is to assess the sleep apnea-hypopnea syndrome through the physiological signals (such as polysomnography) recorded during sleep, and the results are used as an important reference for the diagnosis of sleep disorders. [0003] Traditional SAHS evaluation methods often use template matching to find the salient features of SAHS fragments and calibrate the fragments that meet the standards; however, this t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/11
CPCA61B5/4818A61B5/1135A61B5/7264A61B5/7225A61B5/7203Y02A90/10
Inventor 陈丹张垒明哲锴熊明福
Owner 江西脑调控技术发展有限公司
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