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
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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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