System for identifying fall according to activities of daily living and method thereof

Abstract

The present invention provides a fall sensing system. After motion sensing is performed through a sensing unit, an obtained sensing signal is stored in a storage unit. Then a correcting unit performscorrection on the sensing signal in a physiological signal normalization method and the motion signal normalization method. A motion recognition unit generates motion differentiating data according tothe corrected sensing signal for differentiating different motions. Finally an identification unit determines whether the motion of a user exceeds a falling determining threshold, thereby determininga falling motion. When the motion exceeds the falling determining threshold and the falling motion is determined, the identification unit immediately outputs a signal to a protecting assembly and analarming assembly or one in the protecting assembly and the alarming assembly, thereby immediately performing functions of alarming and protecting when the falling motion of the user occurs.

Description

technical field [0001] The present invention relates to a fall sensing system and method, in particular to a fall sensing system and method for judging a fall action by means of sensing and computing, and immediately providing warning and protection. Background technique [0002] Falls are common accidents in daily life, and they are more frequent in the elderly group. According to a health project in a social development trend survey, falls accounted for 72.8% of the accidents in the elderly group, and the elderly over 65 years old also fell to death. The highest risk group (51.0%). And in a long-term follow-up survey on the physical and social living conditions of middle-aged and elderly people, it was shown that the percentages of those aged 55-64, 65-74, and over 75 who had fallen or fallen in the past year were 14.9%, 19.9%, and 26.5%, respectively, and among them The percentages of fractures, fractures or sprains, and dislocations were 39.4%, 30.7%, and 33.0%, respect...

AI Technical Summary

Problems solved by technology

[0009] Most of the fall sensing protection devices in the prior art use posture or fall action as the judgment basis; thus, due to individual differences in the human body, there are also individual differences in large movements, and the current prior art rarely compares daily life actions with individual differences in the human body. Therefore, it is easy to have the problem that the judgment is not accurate enough;

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