通過運動手表建立學生體質的運動量效模型
發(fā)布時間：2018-11-02 11:25
【摘要】：目的:從心率功能和計步功能的角度對運動手表進行評價,為產品的發(fā)展提供數據;使用運動手表客觀采集學生體力活動參數,獲取膳食營養(yǎng)狀況,建立與學生體質的多元逐步回歸模型。方法:1、運動手表的評測方法。受試者為16名大學生,同時佩戴Polar團隊心率和逸格運動手表,進行4種速度下運動,根據錄像人工計數運動步數。以Polar團隊心率數據與錄像機人工計步數為基準,分別和逸格運動手表相應數據進行相關、回歸分析;得出中等強度運動時心率所對應的步頻范圍。2、身體活動監(jiān)測:受試者為小學3-6年級、初中、高中每年級各12名學生;45名大學生,共計165人;學生佩戴逸格運動手表,每日佩戴運動手表的時間為12小時,共佩戴10天。讀取運動手表中各學生的每日步數,每日步行時間,步頻等運動參數。3、膳食營養(yǎng)調查:連續(xù)進行3天膳食營養(yǎng)調查,對照食物營養(yǎng)成份表,估算營養(yǎng)素攝入量,并與膳食營養(yǎng)推薦攝入量進行比較。4、學生體質測試:依據學生體質測試標準方法,在9月和12月分別對各年級受試者進行2次體質測試,獲取學生體質數據。5、采用多元逐步回歸模型,計算營養(yǎng)和身體活動分別與學生體質成績的相關,并根據相關分析結果進行回歸計算,建立以運動手表數據和營養(yǎng)為自變量,學生體質成績?yōu)橐蜃兞康亩嘣嚓P回歸方程。結果:1、在不同速度下,受試者運動心率(次/min)區(qū)間不同,逸格心率數據集中分布在80-110次/min,逸格運動手表的心率比Polar團隊心率低,且具有顯著性差異(P0.01);在3.2km/h速度下,逸格運動手表的測量步數與錄像機步數相比有顯著性差異(P0.01),隨著測試速度增加,在4.8km/h及以上速度進行運動時,逸格運動手表測量步數與錄像機步數具有較高的一致性(r=0.932);步頻與運動強度具有高度相關性(r=0.938),心率達到中等強度的步頻區(qū)間為[118,148]步/min。2、小學生的步行量和步行時間最大,大學生的中高強度步行量最低;非周末每日步行量顯著高于周末步行量(P0.01);各年級學生的三大能量營養(yǎng)素供能比均在推薦范圍之內;學生每天攝入的維生素B1、維生素C、鈣等均未達到推薦量;肉類、豆類和油脂攝入過多,缺乏奶類及奶制品、蔬菜類的攝入;各年級學生中正常體重人數最低百分比為71.4%;超重和肥胖者占總樣本的20%。3、每日攝入的能量與學生體質總分、BMI得分、立定跳遠評分、坐位體前屈評分、引體向上評分等呈顯著性負相關(P0.05)。每日步行量和每日步行時間與肺活量、50米跑,立定跳遠、坐位體前屈、耐力跑、引體向上等項目的分數呈顯著性正相關(P0.01);學生體質總分與每日攝入能量、蛋白質、脂肪、碳水化合物等的攝入量呈顯著性負相關(P0.05)。4、體質總分與每日步行量的線性模型擬合度較好,采用復合函數模型時,每日步行量的擬合度R2下降了0.005;模型方程為:學生體質總分=96.118-0.732×年齡+0.057×每日步行時間-4.573×性別-0.598×BMI注:年齡范圍:10-19歲;步行時間單位為min/天;BMI單位為:kg/m2;性別:男=1,女=0。驗證結果顯示,運動手表公式計算的學生體質預測值與實測值之間均存在顯著相關性,相關系數為中等(r=0.576),方程的預測值和實測值不存在顯著性差異(P=0.5)。結論:1、在學生日常生活中,能使用步頻表示運動強度,大學生達到中等強度的步頻為118步/min和148步/min。逸格運動手表的計步功能可用于日常步行的測量;測量心率的功能有待優(yōu)化。2、學生體質情況總體較好,步行量與步行時間是影響學生體質的重要因素,體質總分隨步行量增加而上升的趨勢。3、得到學生體質得分預測模型方程。
[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.
【學位授予單位】：南京體育學院
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：G804.49
本文編號：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.
【學位授予單位】：南京體育學院
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：G804.49
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