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Sleep apnea syndrome detection method based on pulse and blood oxygen signals

A technology for sleep apnea and detection methods, which is applied in blood characterization devices, diagnostic recording/measurement, medical science, etc., and can solve the problems of detection accuracy that needs to be improved and few physiological parameters

Inactive Publication Date: 2015-04-29
JILIN UNIV
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Problems solved by technology

Although the above methods are simple and convenient, and have little impact on the sleep of users, they use few physiological parameters, and the detection accuracy needs to be improved.

Method used

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  • Sleep apnea syndrome detection method based on pulse and blood oxygen signals
  • Sleep apnea syndrome detection method based on pulse and blood oxygen signals

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Embodiment Construction

[0009] In order to make the technical solution of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0010] refer to figure 1 Shown is a flow chart of the detection method for sleep apnea syndrome based on the pulse and blood oxygen signals of the present invention.

[0011] Step S101, acquiring pulse and blood oxygen signals.

[0012] Specifically, the pulse and blood oxygen signals of the subjects were continuously recorded throughout the night in a natural sleep state.

[0013] Step S102: Preprocessing the pulse and blood oxygen signals. Specific steps are as follows:

[0014] The collected pulse and blood oxygen signals are divided into minutes to form pulse and blood oxygen signals per unit time, and the binary wavelet modulus maximum algorithm is used to locate the pulse peak per unit time, and the peak-to-peak interval is calculated. The non-unif...

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Abstract

The invention relates to a sleep apnea syndrome detection method based on pulse and blood oxygen signals. The method includes: digging characteristic parameters related to SAS (statistical analysis system) from the pulse and blood oxygen signals by means of probability principal component analysis, setting up an SAS detection characteristic matrix, adopting a pouch decision tree for mapping the relation between the characteristic matrix and SAS disease degrees, and setting up an SAS detection model. By means of probability principal component analysis, input data dimensionality is decreased while quality of the characteristic matrix is improved; owing to the pouch decision tree, SAS detection accuracy is improved; by utilization of the sleep apnea syndrome detection method based on the pulse and blood oxygen signals, the SAS disease degrees of testees can be outputted only by inputting the pulse and blood oxygen signals of the testees.

Description

Technical field: [0001] The invention relates to a sleep apnea syndrome detection method based on pulse and blood oxygen signals, in particular to the application of data dimension reduction technology and supervised learning technology in the classification of sleep apnea syndrome. Background technique: [0002] Sleep apnea syndrome (SAS) has become an invisible killer that endangers human life. According to statistics, the number of SAS patients diagnosed and treated in developed countries is only 20% of the total number of patients, and only 2‰ in my country. The main reason is that the standard detection method PSG is complicated, expensive, and difficult to popularize and apply. Therefore, the study of a convenient and highly accurate detection method to replace PSG will provide strong technical support for the early detection and diagnosis of SAS patients, and has high practical value. [0003] At present, the inventions or innovations of detecting sleep apnea syndrom...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/02A61B5/145
CPCA61B5/4818A61B5/0205
Inventor 李肃义徐壮蒋善庆凌振宝
Owner JILIN UNIV
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