A portable human body fall risk evaluation and early warning system and method thereof

Abstract

The invention discloses a portable human body fall risk evaluation and early warning system and method. The method comprises steps that firstly, an acceleration sensor is utilized to measure and acquire an acceleration signal, and a drift item parameter and a diffusion item parameter are estimated according to an ito equation model; the ito equation model acquired through estimation is utilized to acquire state transfer probability density distribution through utilizing a first time crossing method; lastly, state transfer probability density distribution characteristics are taken as a present fall risk index of an individual, and a matched fall risk grade is outputted. According to the method, a method used for processing non-linear random signals is applied to human bodies, essence rules of motion of human bodies can be represented through data acquired through analysis, and the fall risk index acquired through prediction is more accurate; as the system is simple and convenient, objective quantitative bases can be provided for daily exercises of people. The method is advantaged in that excellent robustness and operation speed are realized, and the fall risk index can be rapidly, comprehensively and accurately evaluated.

Description

technical field [0001] The invention relates to medical early warning equipment, in particular to a portable human body fall risk evaluation and early warning system and an evaluation and early warning method. Background technique [0002] A fall is defined as an unintentional, sudden, involuntary fall of a person from a flat or other fixed, safe position to the floor, ground, or a lower position, including those triggered by syncope or seizures situation. Falls are common among community-dwelling older adults and are fairly common in hospitals and skilled nursing facilities. [0003] Falls are a major medical burden for medical institutions and medical workers. [0004] Every year, 30-40% of the elderly in the community fall at least once, while the proportion of the elderly in professional nursing institutions is three times that of the former. [0005] It is estimated that 2 to 12% of hospitalized patients fall at least once during hospitalization; falls are the most c...

AI Technical Summary

Problems solved by technology

[0010] In order to solve the problem of being unable to objectively quantify the risk of human body falls during exercise, and to provide early warning of fall risk for people with a high risk of falling, the present invention proposes a portable human body fall risk evaluation and early warning system and its evaluation and early warning method to make up for the current lack of early warning of fall risk

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