Intelligent learning type elder falling detection alarm method, device and application

Abstract

The invention discloses an intelligent learning type elder falling detection alarm method, device and application, and the method comprises the steps: taking the set attribute of a detection signal as a triggering condition, and achieving the graded alarm of the falling of an elder in an abnormality prompt and / or remote alarm mode. The device comprises a detection unit, an alarm unit, a storage unit, a power supply unit and a connection unit, the detection unit comprises an acquisition module, an identification module and a processing module, the alarm unit comprises a short message module, a telephone module and a positioning module, and grading alarm is realized by adopting short message pushing, telephone alarm and real-time positioning modes. According to the application, the method is applied to an existing product / service, or other functions are added to the device according to needs so as to enrich user experience and precision user characteristics, support is provided for various pension intervention measures in the future, the effect of alarming, help seeking and escape is truly achieved in emergency, and social harmony can be promoted.

Description

technical field [0001] The invention relates to the technical field of smart elderly care and emergency alarm, in particular to an intelligent learning type elderly fall alarm method, device and application. Background technique [0002] China has a population of 1.4 billion, with 254 million people aged 60 and over. China is rapidly entering an aging society. Shanghai Elderly Falls Epidemiological Death Study has conducted a survey of 5,019 cases of elderly people over 60 years old, showing that the annual incidence of falls is 3.33% for those over 60 years old, and 3.71% for those over 65 years old, of which 52.02% falls occur at home, and the elderly die from falls There were 1593 cases, accounting for 84.87% of the total population's fall deaths. Shanghai has a population of more than 24 million, and the elderly population is about 5 million. A simple calculation shows that there are more than 10 million cases of falls every year among the 250 million elderly people in ...

AI Technical Summary

Problems solved by technology

The falls of the elderly in real life are unpredictable and not repeatable, and a large amount of raw data cannot be obtained

[0005] Second, there is no reliable laboratory data

Because the risk of laboratory simulation of elderly falls is too high, if young volunteers are used for experiments, the data obtained will not be targeted and reliable

[0006] Third, even if there is data, it is not universal

[0009] Existing technical ideas can no longer adapt to and meet the general needs of the masses for fall detection and alarm for the elderly, and we must seek breakthroughs in ideas and innovative methods

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