智能手机内置加速度传感器测量健身跳绳运动能量消耗的研究
发布时间：2018-12-20 08:03
【摘要】：目的:以智能手机内置加速度传感器为基础,对健身跳绳运动的原始加速度信号处理方法进行探讨,以此建立健身跳绳的能耗预测方程,并对其进行验证,进而为智能手机在后续相关研究中的应用奠定基础。方法:选取54名受试者(27男、27女),实验组40人,验证组14人。54名受试者分别同时佩戴1部红米手机和一套气体代谢分析仪(Cosmed K4b2)完成两个部分的测试;测试动作为持续并步跳,(1)第一部分测试为固定频率的测试,受试者先静坐5分钟,再分别以60次/分钟、90次/分钟、120次/分钟的频率完成5分钟的跳绳测试;(2)第二部分测试为建模组的测试,受试者静坐5分钟,接着在1×1米的正方形内进行5分钟的跳绳测试。通过Matlab7.0软件对原始信号进行滤波、去趋势和数据合成;以K4b2能量消耗的实测值作为因变量,采用逐步回归方法建立以手机VM(三轴向量计数值)、年龄、身高、体重等为自变量的预测方程;使用配对t检验、组内相关分析、Bland—Altman图等方法对手机能耗预测方程的准确性进行联合评价。结果:第一部分测试中,60次/分钟、90次/分钟、120次/分钟频率的能量消耗平均值分别为6.37 Kcal/min、8.98Kcal/min、9.76Kcal/min,(P0.05);梅脱值分别为6.00METs/min、8.03 METs/min、8.51METs/min,(P0.05);三种频率均属于大强度运动。三种跳绳频率下男生的能量消耗与女生的能量消耗具有显著性差异;但三种跳绳频率下男生的梅脱与女生的梅脱不具有显著性差异,P值大于0.05。在第二部分测试中,手机VM与跳绳频率存在相关性为0.76(P0.01);手机VM与跳绳能耗的相关系数为0.55;两者呈现中等强度的正相关(P0.01)。建模组手机跳绳能耗预测方程的相关系数R为0.897;判定系数R2为0.804;方程调整后的R2为0.799;方程F检验的相伴概率值P0.01;预测方程回归残差为1.691。配对t检验结果显示校标能耗实测值与手机预测值具有显著性差异(P0.05);组内相关分析的克伦巴赫系数为0.717;Bland—Altman图中只有一个点在一致性限度区间以外,占总点数比例的2.44%,不高于5%的标准。结论:(1)三种频率均属于大强度的体力活动;依据本研究所建立的实验条件,采用120次/分钟的健身跳绳频率相比其他频率的健身效果更为经济有效,也更佳符合人体运动特征。(2)手机垂直轴不适用于健身跳绳运动的监测,而采用加速度三轴传感器对健身跳绳运动的监测更为科学有效。(3)本研究中手机能耗预测值与校标能耗实测值均表现出较好的一致性,智能手机能够对健身跳绳的能量消耗进行较好的预测,可作为补充设备应用到大学生健身跳绳运动的指导和干预中。
[Abstract]:Objective: based on the built-in acceleration sensor of smart phone, the original acceleration signal processing method of fitness rope skipping is discussed, and the energy consumption prediction equation of fitness skipping is established and verified. And then lay a foundation for the application of smart phone in the following related research. Methods: 54 subjects (27 males, 27 females), 40 subjects in the experimental group and 14 subjects in the test group, 54 subjects wore a red rice cell phone and a set of gas metabolism analyzer (Cosmed K4b2) at the same time. (1) the first part of the test was a constant frequency test. The subjects sat for 5 minutes first, and then completed the rope skipping test for 5 minutes at the frequency of 60 times per minute, 90 times per minute and 120 times per minute respectively; (2) the second part of the test is the modeling group. The subjects sit in silence for 5 minutes, and then test the skipping rope for 5 minutes in the square of 1 脳 1 meter. The original signal is filtered by Matlab7.0 software, the trend is removed and the data is synthesized. Taking the measured value of K4b2 energy consumption as dependent variable, the prediction equation of mobile phone VM (triaxial meter), age, height, weight and so on was established by stepwise regression method. The accuracy of mobile phone energy consumption prediction equation was evaluated by paired t test, intra-group correlation analysis and Bland-Altman diagram. Results: in the first part of the test, the average energy consumption of 60, 90 and 120 times per minute frequency was 6.37 Kcal/min,8.98Kcal/min,9.76Kcal/min, (P0.05). Meitou value was 6.00METs / mint 8.03 METs/min,8.51METs/min, (P0.05), and the three frequencies belonged to high intensity exercise. There was significant difference in energy expenditure between boys and girls under three kinds of rope skipping frequency, but there was no significant difference between male and female students in three kinds of rope skipping frequencies (P > 0.05). In the second part, the correlation between mobile phone VM and rope skipping frequency was 0.76 (P0.01), and the correlation coefficient between mobile phone VM and rope skipping energy consumption was 0.55. In the model group, the correlation coefficient R is 0.897; the decision coefficient R 2 is 0.804; the adjusted R2 is 0.799; the associated probability value of equation F test is P 0.01; the regression residual of the prediction equation is 1.691. The result of paired t test showed that there was significant difference between the measured value of calibration energy consumption and the predicted value of mobile phone (P0.05), and the Krenbach coefficient of correlation analysis in group was 0.717; There is only one point in the Bland-Altman diagram, which is outside the range of consistency limits, accounting for 2.44% of the total number of points, and is not higher than the standard of 5%. Conclusion: (1) the three kinds of frequency belong to the physical activity of high intensity; According to the experimental conditions established in this study, the fitness effect of skipping rope frequency of 120 times per minute is more economical and effective than that of other frequencies. (2) the vertical axis of mobile phone is not suitable for the monitoring of skipping exercise. The acceleration triaxial sensor is more scientific and effective in the monitoring of fitness skipping movement. (3) in this study, the predicted value of mobile phone energy consumption is in good agreement with the measured value of calibration energy consumption. Smart phone can predict the energy consumption of skipping rope and can be used as supplementary equipment to guide and intervene in skipping exercise of college students.
【学位授予单位】：四川师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G898.1
本文编号：2387695
[Abstract]:Objective: based on the built-in acceleration sensor of smart phone, the original acceleration signal processing method of fitness rope skipping is discussed, and the energy consumption prediction equation of fitness skipping is established and verified. And then lay a foundation for the application of smart phone in the following related research. Methods: 54 subjects (27 males, 27 females), 40 subjects in the experimental group and 14 subjects in the test group, 54 subjects wore a red rice cell phone and a set of gas metabolism analyzer (Cosmed K4b2) at the same time. (1) the first part of the test was a constant frequency test. The subjects sat for 5 minutes first, and then completed the rope skipping test for 5 minutes at the frequency of 60 times per minute, 90 times per minute and 120 times per minute respectively; (2) the second part of the test is the modeling group. The subjects sit in silence for 5 minutes, and then test the skipping rope for 5 minutes in the square of 1 脳 1 meter. The original signal is filtered by Matlab7.0 software, the trend is removed and the data is synthesized. Taking the measured value of K4b2 energy consumption as dependent variable, the prediction equation of mobile phone VM (triaxial meter), age, height, weight and so on was established by stepwise regression method. The accuracy of mobile phone energy consumption prediction equation was evaluated by paired t test, intra-group correlation analysis and Bland-Altman diagram. Results: in the first part of the test, the average energy consumption of 60, 90 and 120 times per minute frequency was 6.37 Kcal/min,8.98Kcal/min,9.76Kcal/min, (P0.05). Meitou value was 6.00METs / mint 8.03 METs/min,8.51METs/min, (P0.05), and the three frequencies belonged to high intensity exercise. There was significant difference in energy expenditure between boys and girls under three kinds of rope skipping frequency, but there was no significant difference between male and female students in three kinds of rope skipping frequencies (P > 0.05). In the second part, the correlation between mobile phone VM and rope skipping frequency was 0.76 (P0.01), and the correlation coefficient between mobile phone VM and rope skipping energy consumption was 0.55. In the model group, the correlation coefficient R is 0.897; the decision coefficient R 2 is 0.804; the adjusted R2 is 0.799; the associated probability value of equation F test is P 0.01; the regression residual of the prediction equation is 1.691. The result of paired t test showed that there was significant difference between the measured value of calibration energy consumption and the predicted value of mobile phone (P0.05), and the Krenbach coefficient of correlation analysis in group was 0.717; There is only one point in the Bland-Altman diagram, which is outside the range of consistency limits, accounting for 2.44% of the total number of points, and is not higher than the standard of 5%. Conclusion: (1) the three kinds of frequency belong to the physical activity of high intensity; According to the experimental conditions established in this study, the fitness effect of skipping rope frequency of 120 times per minute is more economical and effective than that of other frequencies. (2) the vertical axis of mobile phone is not suitable for the monitoring of skipping exercise. The acceleration triaxial sensor is more scientific and effective in the monitoring of fitness skipping movement. (3) in this study, the predicted value of mobile phone energy consumption is in good agreement with the measured value of calibration energy consumption. Smart phone can predict the energy consumption of skipping rope and can be used as supplementary equipment to guide and intervene in skipping exercise of college students.
【学位授予单位】：四川师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G898.1
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