YOU Yonghao,Shao Mengni,HU Yanjie,ZHANG Yang,WANG Guanglei,ZHU Jingjing.Early Warning Model of Fall Risk for the Elderly Based on Gait Characteristics[J].Journal of medical biomechanics,2020,35(4):357-363
基于步态特征的老年人跌倒风险预警模型
Early Warning Model of Fall Risk for the Elderly Based on Gait Characteristics
Received:July 03, 2019  Revised:August 28, 2019
DOI:
Chinese key words:  步态测试  行走方式  跌倒风险  预警模型
English Key words:gait test  walking mode  fall risk  early warning model
Fund project:2016年度安徽高校自然科学研究重点项目(KJ2016A582),2020年度安徽高校自然科学研究重点项目(KJ2020A0129)
Author NameAffiliation
YOU Yonghao Department of Sports Science Hefei Normal University 
Shao Mengni Department of Sports Science Hefei Normal University 
HU Yanjie Department of Neurology, the Second Affiliated Hospital of Anhui Medical University 
ZHANG Yang Department of Sports Science Hefei Normal University 
WANG Guanglei Department of Sports Science Hefei Normal University 
ZHU Jingjing Department of Sports Science Hefei Normal University 
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Chinese abstract:
      目的 根据6种步态的测试参数分别构建老人跌倒风险预警模型。方法 使用数字化场地采集有跌倒史和无跌倒史老年人的6种步态参数,采用二项logistic回归分析法,建立预测老人跌倒风险的回归方程,构建跌倒预警模型。结果 根据6种步态的测试参数所构建的回归方程均具有统计学意义,预测总体正确率由高到底依次为:闭眼正走(97.1%)、睁眼倒走(92.9%)、闭眼倒走(88.6%)、睁眼正走(87.1%)、睁眼上下转头(85.7%)、睁眼左右转头(82.9%)。所构建的老年人跌倒风险预警模型主要包括判定、测试、提取、计算、预警5个步骤,适合在实验室内对老年人进行步态测试与跌倒风险评估。结论 6种步态的测试参数都能够预测老年人的跌倒风险,其中闭眼正走的预测效果最好,是预测老年人跌倒风险的最佳步态。所构建的老年人跌倒风险预警模型用于预测65~75岁老年人1年内的跌倒风险,并可根据跌倒概率发出预警,对预防老年人跌倒具有积极作用。
English abstract:
      Objective To construct an early warning model of fall risk for the elderly based on six kinds gait parameters. Methods A digital field was used to collect parameters from six kinds of gait for the elderly with or without the history of falls, and the binomial logistic regression analysis was used to establish a regression equation for predicting the fall risks in the elderly, and an early warning model was constructed. Results The regression equations constructed according to the parameters from six kinds of gait were statistically significant. The overall correct rate was predicted from high to low: walking forward with closed eyes (97.1%), walking backward with open eyes (92.9%), walking backward with closed eyes (88.6%), walking forward with open eyes (87.1%), turning head up and down with open eyes (85.7%), turning head left and right with open eyes(82.9%). The constructed early warning model for fall risk of the elderly mainly included five steps, namely, judgment, test, extraction, calculation and early warning, which was suitable for gait testing and evaluation of the elderly in the laboratory. Conclusions Parameters from six kinds of gait could predict the fall risk of the elderly. Among them, walking forward with closed eyes was best to predict the fall risk in the elderly. The established early warning model of fall risk for the elderly could be used to predict the fall risk of 65-75 year old people within one year, which could provide early warning based on the probability of falling, playing a positive effect on preventing falls in the elderly.
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