Statistical Research On Dual-task Performance Of Computational Ability And Gait Of Middle-aged And Old People Over 50 Years Old

Objective: To study the distribution of computing power of middleaged and elderly people over 50 years old in my country and its influencing factors,and to further study the quantitative relationship between gait and computing power of middle-aged and elderly people of different ages and education levels.Method: This project takes a medical center in a central and western city as the experimental site,and is generally carried out in two stages.The first stage: A total of 472 subjects who met the inclusion and exclusion criteria and signed the informed consent form were included.The subjects performed the "serial subtraction-walking" dual-task test with a timing of 1 minute.The experimenters nearby recorded their calculation results.They also needed to collect their general demographic information,MMSE screening scale and other data.In the data analysis stage,multiple regression analysis,non-parametric hypothesis testing and other methods are used to study the influence of gender,age,education level on the computing power of middle-aged and elderly people,and the correct number of quantiles for different age groups are given through the Bootstrap method.The second stage: a total of 334 subjects who met the inclusion and exclusion criteria and signed the informed consent form were included.The subjects were required to wear a sensor device to collect their gait signals,and perform the "serial subtraction-walking" dual-task test with a timing of 1 minute and the "walking" single-task test with a timing of 1 minute.The calculation results are recorded by field experimenters,and the gait signals are recorded in real time by wearable devices.In the data analysis stage,the gait signal processing method is mainly used to analyze and compare the gait difference between single-task and dual-task walking from the three aspects of the number of steps,the coefficient of variation of stride time,and the coefficient of variation of acceleration.Calculate the correct relationship between subgroups of different ages and education levels.Results: Through Wilcoxon test the relationship between computing power score and gender,P=0.265>0.05;further non-parametric hypothesis tests were performed on age and education level factors,and P values were 0.016 and 5.1294*10-14.The test result of the correlation between computing power level and MMSE score for each subject was P=0.001<0.05.The regression equation obtained by the multiple regression analysis is: dual-task computing power score = 21.813 +(-0.178)* age +(-0.953)* gender(male: 1;female: 2)+ 0.809 * education level.The average values of the step difference between the single and double tasks in the 0-10,10-20,20-30,30-40 calculation correct array are:-5.00,-3.82,-0.13,1.38.Conclusion: Education level,age,and gender are possible factors that affect the computing power of middle-aged and elderly people,and the level of influence decreases sequentially.Among them,gender has the least significant impact on the computing power of middle-aged and elderly people,and the computing power level is the same The MMSE score has a strong correlation.In addition,in the decline in age-related gait,the decline is more obvious for people with low computing power;and for middle-aged and elderly people,the stronger their computing ability,the better their walking ability,and in older people,this rule is more obvious.