Human body fall-down prevention early warning and intervening method and system

Abstract

The invention relates to the technical field of human body fall-down detecting and intervening and provides a human body fall-down prevention early warning and intervening method and system. The human body fall-down prevention early warning and intervening method includes the steps that real-time detection is performed on the body posture of a monitored object, body posture information of the monitored object is collected, and detection data are obtained; fusion processing is performed on the detection data so as to obtain the processed signal data; the processed signal data are compared with a set threshold so as to judge whether the monitored object inclines to fall down or not, and when the monitored object inclines to fall down, early warning information is sent out before the monitored object falls down; fall-down prevention shoes work, intervening measures are carried out, and fall-down prevention is performed. The human body fall-down prevention early warning and intervening method and system achieve early warning and intervening before the human body falls down.

Description

【Technical field】 [0001] The invention relates to the technical field of human body fall detection and intervention, in particular to a human body fall prevention early warning and intervention method and system. 【Background technique】 [0002] A fall is defined as a sudden, involuntary, involuntary change in position, such as falling onto the ground or a lower surface. According to statistics, about 424,000 deaths are directly related to falls every year in the world, and falls are the second leading cause of unintentional injury deaths in the world (after traffic accidents). Studies have shown that among the elderly over 65 years old, the proportion of one or more falls per year is as high as 1 / 3, and 20-30% of them will cause abrasions, hip fractures, head fractures, etc. during falls. Trauma, etc., and increase with age. In the United States, the total medical cost of falls exceeds $20 billion per year. There are currently about 130 million elderly people in my countr...

AI Technical Summary

Problems solved by technology

[0004] (1) Analysis based on video images: The real-time movement of the object is monitored by the camera, and its disadvantage is that it cannot guarantee the privacy of the user;

[0005] (2) Analysis based on audio frequency signals: the fall event is judged by analyzing the frequency of the vibration caused by the impact, but its installation is more complicated and the capital investment is relatively large;

[0008] (1) The early warning before the fall is not realized: the current common "fall alarm", the sensing module generally uses a single three-axis accelerometer, the measurement accuracy and data mode are limited, or the threshold algorithm used is not good enough , so it can only realize the alarm function after the human body falls and cannot realize the early warning before the fall, so it is impossible to realize the immediate anti-fall intervention measures and real-time protection;

[0009] (2) Effective intervention before falls is not achieved: As mentioned above, since the current common fall alarms cannot achieve accurate warnings, it is unlikely to achieve immediate fall prevention interventions;

[0010] (3) The accuracy of fall judgment is not ideal: most of the current fall judgment devices mainly rely on acceleration to judge the occurrence of fall events, but the daily movement of the human body is very complicated, and falls are usually accidental behaviors that occur in an instant (1-2 Seconds), the reliability of predicting falls by relying on less or a single human body movement and posture information is not high. Misjudgment will inevitably bring inconvenience to the wearer

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