Health condition predicting method based on data mining and device thereof

Abstract

An embodiment of the invention provides a health condition predicting method based on data mining and a device thereof. The method comprises the steps of obtaining a physiological parameter which corresponds with the current time of a to-be-tested user; performing characteristic extraction on the physiological parameter for obtaining a random item or combination of corresponding offset degree, instantaneous variance and drift degree; constructing a long-term change trend according to the offset degree, constructing a short-time change violence according to the instantaneous variance, and constructing long-term drift degree according to the drift degree; constructing a danger early-warning factor according to the long-term change trend, the short-time change violence and the long-term driftdegree, and predicating the health condition of the to-be-tested user through the constructed danger early-warning factor and the predicating model for obtaining a predicating result. The device is used for executing the method. According to the health condition predicating method, the corresponding characteristic parameter is obtained through performing characteristic extracting on the physiological parameter; the danger early-warning factor is constructed according to the characteristic parameter; and a predication result is obtained by means of the prediction model, thereby effectively reducing an error prediction rate in a monitoring process.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of data mining, and in particular to a method and device for predicting health status based on data mining. Background technique [0002] With the continuous development of mobile medical and health equipment such as wearables, wrist watches, and mattresses, the current nursing home monitoring system can realize continuous, real-time, and long-term monitoring of various vital signs of the elderly through these equipments, and realize the monitoring of the elderly. Health monitoring and abnormal situation alarm. [0003] In the alarm of the abnormal health status of the elderly, the existing monitoring equipment usually uses a simple threshold alarm method for abnormal alarm. This method can easily lead to false alarms for the dangerous status of the elderly. The signal is overly tense or mistrusted, and underreporting may even delay the real condition of the elderly. At present, o...

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Problems solved by technology

[0003] In the alarm of the abnormal health status of the elderly, the existing monitoring equipment usually uses a simple threshold threshold alarm method for abnormal alarm. Excessive nervousness or distrust of signals, and underreporting may even delay the real condition of the elderly

At present, only a few monitoring systems can establish a personalized model for a certain individual and a certain type of physiological data for risk warning, but for different elderly people, there are certain individual differences in their physiological indicators, and different physiological data also have different effects. characteristics, such personalized models are not widely applicable

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