Detecting device and method of unstable motion data

Abstract

The invention discloses a detecting device and method of unstable motion data. The detecting device comprises an unstable motion simulation platform and a human body motion data detecting device, wherein the unstable motion simulation platform is used for guiding human body motions, so that a human body is in an unstable state, and the human body motion data detecting device is used for measuringand recording motion parameters and gait parameters of the human body on the unstable motion simulation platform. The invention further discloses the detecting method of the unstable motion data, andthe method comprises the steps that the generation of the instability of the human body is guided by adopting the unstable motion simulation platform; the motion parameters and the gait parameters ofthe human body are measured and recorded by using the human body motion data detecting device. By means of the unstable motion data detecting device, the motion state of a participant is detected. Byusing the unstable motion simulation platform, different unstable motion states are generated, the motion parameters of the participant are detected in real time, and a parametric basis is provided for subsequent accurate evaluation of falling risks of the human body.

Description

technical field [0001] This application relates to destabilizing motion, in particular to a detection device and method for destabilizing motion data. Background technique [0002] Because the human body loses its balance, it may lead to falls, which may be caused by itself or by external factors. When the human body loses its balance, it will carry out a self-regulation process under the action of the human body's instinct. The result after self-regulation undoubtedly has two possibilities: one is to restore the balance, and the other is to fall to the ground. Fall is also a kind of human body motion state, and fall is usually defined as: the human body falls on the ground or other lower planes due to sudden and involuntary posture changes. When the human body experiences a fall, it will sequentially go through three stages: instability, hitting the ground, and stabilization. Therefore, the risk assessment of human falls is to evaluate the adjustment ability of the human ...

AI Technical Summary

Problems solved by technology

① Insufficient accuracy of fall risk assessment for the elderly: Existing analysis found that no matter for the elderly in the community or hospitalized patients, the existing fall risk assessment tools cannot effectively predict the number of falls

② These assessment tools usually require multidisciplinary professionals, specific examination sites and equipment, and the assessment results depend to a certain extent on the experience of the assessing doctor, thus greatly limiting their scope of application

③The assessment of exercise capacity is all completed in a specific examination room. On the one hand, there is an experimenter effect (Hawthorne effect). On the other hand, the experimental environment is far from the daily life environment of the elderly, which affects the accuracy of fall prediction.

④The use of questionnaires and functional tests often lacks objectivity and accuracy due to the subjective judgment of testers and subjects

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