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Sleeping data analysis method for stroke prediction

A technology of data analysis and sleep, applied in diagnostic recording/measurement, medical science, sensors, etc., to achieve the effect of improving accuracy, accurate prediction, and reducing false negative rate

Inactive Publication Date: 2018-11-09
NORTHWESTERN POLYTECHNICAL UNIV
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  • Abstract
  • Description
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Problems solved by technology

For example, electrocardiogram users wear multiple professional sensor devices and are assisted by professionals to obtain data, while electroencephalograms require professionals to use more expensive medical equipment to obtain

Method used

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  • Sleeping data analysis method for stroke prediction
  • Sleeping data analysis method for stroke prediction
  • Sleeping data analysis method for stroke prediction

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Embodiment Construction

[0032] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings.

[0033] The present invention has 2 accompanying drawings, please refer to figure 1 As shown, the specific process of a sleep data analysis method for stroke prediction of the present invention is as follows:

[0034] Step 1: Participants were obtained from their past electronic medical records and completed questionnaires: age, sex, diastolic blood pressure, systolic blood pressure, hypertension, total cholesterol, HDL cholesterol, etc.

[0035] Step 2: Obtain the biorhythm data of participants' sleep throughout the night through smart devices, and go through a sleep cycle in about 90 to 100 minutes. A sleep cycle includes 5 different stages: awakening period, light sleep period, deep sleep period, and deep sleep period, rapid eye movement period. Construct the sleep data model of individual participants, expressed as formula (1)

[0036] ...

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Abstract

The invention provides a sleeping data analysis method for stroke prediction. The potential risk is found as soon as possible by analyzing the sleeping time, the sleeping efficiency, light sleep, deepsleep and other changes in the sleeping cycle and the sleeping stage of a participant, besides, after a prediction result is obtained with a common prediction model, the result is further processed in a similarity principle, so that the missing report rate is reduced, and the missing report rate is controlled in a receptible range. Compared with the prior art, continuous long-time sleeping data of the participator are acquired in a convenient and non-invasion manner, the stroke risk of the participator can be more accurately predicted in combination with part of known clinical physiological data. Meanwhile, by means of the method, the accurate rate of known prediction models can be increased by calculating the similarity of the participator with crowds suffering from stroke and crowds without stroke.

Description

technical field [0001] The invention relates to the field of stroke disease prediction, in particular to a sleep data analysis method for stroke prediction. Background technique [0002] "Stroke" is also called "stroke". Clinical mainly refers to cerebral hemorrhage, cerebral thrombosis and so on. Its morbidity rate, disability rate, and mortality rate are all in the forefront in the world, and it is a group of diseases that seriously endanger people's health. It is an important means of stroke prevention to objectively assess the risk of stroke based on relevant characteristics and to identify high-risk groups in advance, so that the target population for key prevention can be more concentrated, and it can help promote the rational use of public health resources, which is of great help in reducing the incidence of stroke. rates and mortality are of great significance. Although prediction models for cardiovascular disease or stroke have been established at home and abroad...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00
CPCA61B5/4806A61B5/4812A61B5/7235A61B5/7275
Inventor 王柱於志文谢佳郭斌周兴社
Owner NORTHWESTERN POLYTECHNICAL UNIV
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