Chronic disease patient health trend monitoring and early warning system

Abstract

The invention discloses a chronic disease patient health trend monitoring and early warning system. According to the technical scheme, the system comprises a pressure collecting module, a data processing module and an early warning and alarming module, the pressure collecting module is formed by distributing a plurality of pressure sensors in a matrix mode and used for obtaining multi-dimensional pressure signals representing vital sign parameters; the data processing module is used for fusing the multi-dimensional pressure signal data to obtain one-dimensional dynamic indexes; a dynamic graph model is established by taking a plurality of continuous index points as nodes of the graph model; optimization indexes are calculated through the dynamic graph model; the early warning and alarm module is used for comparing the optimization index with a threshold value so as to carry out trend early warning; and abnormity alarm is performed based on a hypothesis testing method. According to the invention, through modular design, a monitoring pad can be flexibly matched to realize vital sign state monitoring; and the module is built based on the dynamic graph model, monitoring data can be processed in real time to obtain optimization indexes, and corresponding early warning and alarm can be given according to different types of data overrun or abnormal states.

Description

technical field [0001] The invention relates to the field of health monitoring systems, in particular to a health trend monitoring and early warning system for patients with chronic diseases. Background technique [0002] At present, for some patients with chronic diseases, such as epilepsy, the onset time is random and unpredictable, requiring long-term real-time monitoring. The inventor found that common home monitoring equipment includes monitoring bracelets, wearable electrode monitoring equipment, video surveillance equipment, etc. Since home monitoring often requires wearing or binding equipment, it has a certain impact on normal life and poor comfort; not applicable Sleep monitoring at night. Surveillance devices have poor privacy protection and consume a lot of energy. At the same time, these monitoring devices have low real-time performance and cannot give early warning of health trends. [0003] Moreover, the existing pressure pad products have few measuring poi...

AI Technical Summary

Problems solved by technology

[0002] At present, for some patients with chronic diseases, such as epilepsy, the onset time is random and unpredictable, requiring long-term real-time monitoring

The inventor found that common home monitoring equipment includes monitoring bracelets, wearable electrode monitoring equipment, video surveillance equipment, etc. Since home monitoring often requires wearing or binding equipment, it has a certain impact on normal life and poor comfort; not applicable sleep monitoring at night

Surveillance devices have poor privacy protection and consume a lot of energy

At the same time, these monitoring devices have low real-time performance and cannot give early warnings of health trends.

[0003] Moreover, the existing pressure pad products have few measuring points and poor real-time performance. They mainly conduct static pressure distribution analysis, relying on visual observation and empirical subjective decision-making, which consume a lot of time and energy, and cannot realize real-time monitoring and early warning.

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