Tumble detection method

Abstract

The invention discloses a tumble detection method, which comprises the following steps of S1, performing acceleration calculation on data acquired by a three-axis acceleration sensor, determining a threshold range through a BP neural network, and comparing whether the acceleration exceeds or not to judge whether the current movement of a human body is abnormally intense or not; s2, further calculating the relative energy loss of the human bodyd by multiplying the acceleration data calculated in the step S1 by time and integrating the time, and comparing whether the relative energy loss exceeds a set threshold value or not to judge whether the current movement of the human body is abnormally intense or not; and S3, acquiring data by using a three-axis gyroscope, calculating an inclination angle and a roll angle of the human body through a Kalman filtering algorithm, and determining whether the posture of the human body is abnormal by judging whether the inclination angle and the roll angle exceed set thresholds. According to the invention, the reliability of an output result is improved through the multi-stage tumble judgment, the possibility of misjudgment and omission in a judgment algorithm is reduced as much as possible, and the system has the capability of self-adaption according to the characteristics of a user.

Description

technical field [0001] The invention belongs to the technical field of health monitoring and relates to a fall detection method. Background technique [0002] Most of the existing elderly monitoring systems accumulate a large amount of user health data for a long time, and then mine and analyze these data. The cycle is too long and the cost is too high. This type of monitoring system often has complex structural design, slow data processing, and low efficiency, and cannot meet the needs of elderly caregivers to obtain emergency situations such as falls in a timely manner. As people pay more attention to health, in the care and health management of the elderly or patients, how to improve the efficiency of care, save the labor cost of care, and detect the abnormalities of the elderly or patients at the first time is the current Issues to be solved urgently in nursing and health management. In the event of a fall, timely and accurate fall detection and alarm can win valuable ...

AI Technical Summary

Problems solved by technology

[0002] Existing monitoring systems for the elderly are mostly based on long-term accumulation of a large amount of user health data, and mining and analysis of these data, the cycle is too long and the cost is too high

This type of monitoring system often has complex structural design, slow data processing, and low efficiency, which cannot meet the needs of elderly caregivers for timely access to emergency situations such as falls.

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