通过运动手表建立学生体质的运动量效模型
发布时间：2018-11-02 11:25
【摘要】：目的:从心率功能和计步功能的角度对运动手表进行评价,为产品的发展提供数据;使用运动手表客观采集学生体力活动参数,获取膳食营养状况,建立与学生体质的多元逐步回归模型。方法:1、运动手表的评测方法。受试者为16名大学生,同时佩戴Polar团队心率和逸格运动手表,进行4种速度下运动,根据录像人工计数运动步数。以Polar团队心率数据与录像机人工计步数为基准,分别和逸格运动手表相应数据进行相关、回归分析;得出中等强度运动时心率所对应的步频范围。2、身体活动监测:受试者为小学3-6年级、初中、高中每年级各12名学生;45名大学生,共计165人;学生佩戴逸格运动手表,每日佩戴运动手表的时间为12小时,共佩戴10天。读取运动手表中各学生的每日步数,每日步行时间,步频等运动参数。3、膳食营养调查:连续进行3天膳食营养调查,对照食物营养成份表,估算营养素摄入量,并与膳食营养推荐摄入量进行比较。4、学生体质测试:依据学生体质测试标准方法,在9月和12月分别对各年级受试者进行2次体质测试,获取学生体质数据。5、采用多元逐步回归模型,计算营养和身体活动分别与学生体质成绩的相关,并根据相关分析结果进行回归计算,建立以运动手表数据和营养为自变量,学生体质成绩为因变量的多元相关回归方程。结果:1、在不同速度下,受试者运动心率(次/min)区间不同,逸格心率数据集中分布在80-110次/min,逸格运动手表的心率比Polar团队心率低,且具有显著性差异(P0.01);在3.2km/h速度下,逸格运动手表的测量步数与录像机步数相比有显著性差异(P0.01),随着测试速度增加,在4.8km/h及以上速度进行运动时,逸格运动手表测量步数与录像机步数具有较高的一致性(r=0.932);步频与运动强度具有高度相关性(r=0.938),心率达到中等强度的步频区间为[118,148]步/min。2、小学生的步行量和步行时间最大,大学生的中高强度步行量最低;非周末每日步行量显著高于周末步行量(P0.01);各年级学生的三大能量营养素供能比均在推荐范围之内;学生每天摄入的维生素B1、维生素C、钙等均未达到推荐量;肉类、豆类和油脂摄入过多,缺乏奶类及奶制品、蔬菜类的摄入;各年级学生中正常体重人数最低百分比为71.4%;超重和肥胖者占总样本的20%。3、每日摄入的能量与学生体质总分、BMI得分、立定跳远评分、坐位体前屈评分、引体向上评分等呈显著性负相关(P0.05)。每日步行量和每日步行时间与肺活量、50米跑,立定跳远、坐位体前屈、耐力跑、引体向上等项目的分数呈显著性正相关(P0.01);学生体质总分与每日摄入能量、蛋白质、脂肪、碳水化合物等的摄入量呈显著性负相关(P0.05)。4、体质总分与每日步行量的线性模型拟合度较好,采用复合函数模型时,每日步行量的拟合度R2下降了0.005;模型方程为:学生体质总分=96.118-0.732×年龄+0.057×每日步行时间-4.573×性别-0.598×BMI注:年龄范围:10-19岁;步行时间单位为min/天;BMI单位为:kg/m2;性别:男=1,女=0。验证结果显示,运动手表公式计算的学生体质预测值与实测值之间均存在显著相关性,相关系数为中等(r=0.576),方程的预测值和实测值不存在显著性差异(P=0.5)。结论:1、在学生日常生活中,能使用步频表示运动强度,大学生达到中等强度的步频为118步/min和148步/min。逸格运动手表的计步功能可用于日常步行的测量;测量心率的功能有待优化。2、学生体质情况总体较好,步行量与步行时间是影响学生体质的重要因素,体质总分随步行量增加而上升的趋势。3、得到学生体质得分预测模型方程。
[Abstract]:Objective: To evaluate sports watch from the angle of heart rate function and counting function, and to provide data for the development of product. Methods: 1. Evaluation method of sports watch. The subject was a 16 college student while wearing a Polar team heart rate and an escape watch, moving at 4 speeds and manually counting the number of movements according to the video. correlation and regression analysis were carried out with the Polar group heart rate data and the number of manual count steps of the video recorder, respectively, and the pacing range corresponding to the heart rate during moderate intensity exercise was obtained. 2. Physical activity monitoring: The subjects were Grade 3-6 in primary school and junior middle school. High school each year 12 students; 45 college students, a total of 165; students wear escape sports watches, wear sports watches daily for 12 hours, wear 10 days. reading the daily steps of each student in the sports watch, daily walking time, step frequency and other sports parameters; 3, dietary nutrition investigation: continuously carrying out three-day dietary nutrition survey, controlling the nutrient composition table of the food, estimating the nutrient intake, and comparing with the dietary nutrition recommendation intake; 4, student body constitution test: according to the standard method of student body constitution test, in September and December, each grade subject carries out two physical tests, obtains student's physical fitness data. 5, uses multiple stepwise regression model, calculates nutrition and physical activity respectively related to student's physical performance, According to the correlation analysis result, the regression calculation is carried out, and the data and nutrition of the sports watch are established as independent variables, and the student's physique score is the multivariate correlation regression equation of the variable. Results: 1. Under different velocity, the heart rate (bpm) interval of the subjects was different, the concentration of the escape rate data was 80-110 times/ min, the heart rate was lower than that of the Polar group, and there was significant difference (P0.01); at the speed of 3. 2km/ h, There is a significant difference between the number of measured steps and the number of steps of the video recorder (P0.01). With the increase of the test speed, the number of steps taken by the runaway watch is consistent with the number of steps of the video recorder (r = 0.9932). The step frequency and the intensity of movement have a high correlation (r = 0. 938), the step frequency interval of the heart rate reaching the medium intensity is[118, 148] step/ min. 2, the walking amount and walking time of the primary school students are the largest, the middle strength walking amount of the college students is the lowest, and the daily walking amount of the non-weekend is significantly higher than the weekend walking amount (P0.01); The three major energy nutrient supply ratios of each grade student are within the recommended range; the daily intake of vitamin B1, vitamin C, calcium, etc. has not reached the recommended amount; the intake of meat, beans and oil is too much, and the intake of milk and dairy products and vegetables is lack; The lowest percentage of normal weight in all grade students was 71.4%; overweight and obese accounted for 20% of the total samples; 3. The daily intake energy was negatively correlated with student's physical score, BMI score, standing long jump score, pre-seat flexion score, body-up score, etc. (P0.05). The daily walking distance and daily walking time were positively correlated with the scores of vital capacity, 50-meter running, standing long jump, pre-sitting flexion, endurance running, leading-up and the like (P0.01); the total scores of students' physical constitution were related to daily intake energy, protein and fat. There was a significant negative correlation between the intake of carbohydrate and the like (P0.05). Student's physical fitness score = 96. 118-0.732 bpm age + 0.057 bpm daily walking time-4,573,057 bpm BMI Note: Age range: 10-19 years; walking time unit min/ day; BMI unit: kg/ m2; gender: male = 1, female = 0. The results showed that there was a significant correlation between the predicted value of the student's constitution and the measured value, and the correlation coefficient was moderate (r = 0. 576), and there was no significant difference between the predicted value of the equation and the measured value (P = 0.05). Conclusion: 1. In the daily life of students, the step frequency can be used to express the intensity of movement, and the step frequency of the college students reaching medium strength is 118 steps/ min and 148 steps/ min. the meter step function of the escape sports watch can be used for the daily walking measurement; the function of measuring heart rate is to be optimized; 2, the physical condition of the students is generally good, the walking amount and the walking time are important factors which influence the physical fitness of the students, and the physical fitness total score increases with the increase of the walking amount. 3, and obtaining a student body constitution score prediction model equation.
【学位授予单位】：南京体育学院
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G804.49
本文编号：2305874
[Abstract]:Objective: To evaluate sports watch from the angle of heart rate function and counting function, and to provide data for the development of product. Methods: 1. Evaluation method of sports watch. The subject was a 16 college student while wearing a Polar team heart rate and an escape watch, moving at 4 speeds and manually counting the number of movements according to the video. correlation and regression analysis were carried out with the Polar group heart rate data and the number of manual count steps of the video recorder, respectively, and the pacing range corresponding to the heart rate during moderate intensity exercise was obtained. 2. Physical activity monitoring: The subjects were Grade 3-6 in primary school and junior middle school. High school each year 12 students; 45 college students, a total of 165; students wear escape sports watches, wear sports watches daily for 12 hours, wear 10 days. reading the daily steps of each student in the sports watch, daily walking time, step frequency and other sports parameters; 3, dietary nutrition investigation: continuously carrying out three-day dietary nutrition survey, controlling the nutrient composition table of the food, estimating the nutrient intake, and comparing with the dietary nutrition recommendation intake; 4, student body constitution test: according to the standard method of student body constitution test, in September and December, each grade subject carries out two physical tests, obtains student's physical fitness data. 5, uses multiple stepwise regression model, calculates nutrition and physical activity respectively related to student's physical performance, According to the correlation analysis result, the regression calculation is carried out, and the data and nutrition of the sports watch are established as independent variables, and the student's physique score is the multivariate correlation regression equation of the variable. Results: 1. Under different velocity, the heart rate (bpm) interval of the subjects was different, the concentration of the escape rate data was 80-110 times/ min, the heart rate was lower than that of the Polar group, and there was significant difference (P0.01); at the speed of 3. 2km/ h, There is a significant difference between the number of measured steps and the number of steps of the video recorder (P0.01). With the increase of the test speed, the number of steps taken by the runaway watch is consistent with the number of steps of the video recorder (r = 0.9932). The step frequency and the intensity of movement have a high correlation (r = 0. 938), the step frequency interval of the heart rate reaching the medium intensity is[118, 148] step/ min. 2, the walking amount and walking time of the primary school students are the largest, the middle strength walking amount of the college students is the lowest, and the daily walking amount of the non-weekend is significantly higher than the weekend walking amount (P0.01); The three major energy nutrient supply ratios of each grade student are within the recommended range; the daily intake of vitamin B1, vitamin C, calcium, etc. has not reached the recommended amount; the intake of meat, beans and oil is too much, and the intake of milk and dairy products and vegetables is lack; The lowest percentage of normal weight in all grade students was 71.4%; overweight and obese accounted for 20% of the total samples; 3. The daily intake energy was negatively correlated with student's physical score, BMI score, standing long jump score, pre-seat flexion score, body-up score, etc. (P0.05). The daily walking distance and daily walking time were positively correlated with the scores of vital capacity, 50-meter running, standing long jump, pre-sitting flexion, endurance running, leading-up and the like (P0.01); the total scores of students' physical constitution were related to daily intake energy, protein and fat. There was a significant negative correlation between the intake of carbohydrate and the like (P0.05). Student's physical fitness score = 96. 118-0.732 bpm age + 0.057 bpm daily walking time-4,573,057 bpm BMI Note: Age range: 10-19 years; walking time unit min/ day; BMI unit: kg/ m2; gender: male = 1, female = 0. The results showed that there was a significant correlation between the predicted value of the student's constitution and the measured value, and the correlation coefficient was moderate (r = 0. 576), and there was no significant difference between the predicted value of the equation and the measured value (P = 0.05). Conclusion: 1. In the daily life of students, the step frequency can be used to express the intensity of movement, and the step frequency of the college students reaching medium strength is 118 steps/ min and 148 steps/ min. the meter step function of the escape sports watch can be used for the daily walking measurement; the function of measuring heart rate is to be optimized; 2, the physical condition of the students is generally good, the walking amount and the walking time are important factors which influence the physical fitness of the students, and the physical fitness total score increases with the increase of the walking amount. 3, and obtaining a student body constitution score prediction model equation.
【学位授予单位】：南京体育学院
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G804.49
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