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Human body maximum oxygen uptake evaluation method and application based on BP neural network

A BP neural network and oxygen uptake technology, which is applied in the field of human body fitness detection, can solve the problems of not performing SEE estimation, and achieve high practical value, high accuracy, and simple and easy measurement

Inactive Publication Date: 2017-01-04
王伟
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The equation was established by McCole et al. from the Department of Sports Science of the University of Florida in the United States by using the same bicycle, the same tire pressure, and the control speed (32‐40Km / h) on 92 testers to establish a regression equation. It has been verified that its correlation The coefficient r value is 0.84, but it has not been estimated by SEE

Method used

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  • Human body maximum oxygen uptake evaluation method and application based on BP neural network
  • Human body maximum oxygen uptake evaluation method and application based on BP neural network
  • Human body maximum oxygen uptake evaluation method and application based on BP neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0056] Embodiment 1. The establishment of the maximum oxygen uptake BP neural network model

[0057] Select 40 subjects, including 20 men and women, aged 20-36, test the age and weight of all subjects, and test the time for all subjects to complete the 1600-meter run at a uniform speed at the maximum speed in the same track and field field. Immediately after running, use the Polar meter to test the heart rate per minute; then standardize the four data collected by the subject's age, weight, 1600-meter running time, and heart rate immediately after running according to formula (I), and obtain a result greater than or equal to 0, Data less than or equal to 1;

[0058] x i ¯ = x i - x min x m a x - ...

Embodiment 2

[0063] Embodiment 2. The establishment of the maximum oxygen uptake BP neural network model

[0064] Select 100 subjects, including 50 men and women, aged 25-35, test the weight and height of all subjects, and test the time for all subjects to complete the 1600-meter run at a uniform speed at the maximum speed in the same track and field field. Immediately after running, use the Polar watch to test the heart rate per minute; then standardize the five data collected by the subject's age, weight, height, 1600-meter running time, and heart rate immediately after running according to formula (I), and get greater than or equal to 0, data less than or equal to 1.

[0065] x i ¯ = x i - x min x max - x min ...

Embodiment 3

[0071] Embodiment 3. Human body maximum oxygen uptake evaluation based on BP neural network model

[0072] A method for evaluating human body maximum oxygen uptake based on BP neural network, the specific steps are as follows:

[0073] 1) Measure the height and weight of 200 students from Tsinghua University and nearby community residents using height rulers and weighing scales, and at the same time obtain the gender and age information of the subjects; test the subjects in the same venue and complete the 1600 at a uniform speed at the maximum speed Use the Polar watch to measure the heart rate per minute immediately after running;

[0074] 2) Using gender, height, age, weight, time of running 1600 meters and heart rate data immediately after running as parameters, use the BP neural network model ANN2 established in Example 1 to measure and calculate the maximum oxygen uptake of the subject;

[0075] 2.1) Standardize the data and information obtained in step 1) for preprocess...

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Abstract

The present invention provides a human body maximum oxygen uptake evaluation method based on a BP neural network. The method comprises the following steps: collecting subject's data, wherein the data includes the weight, the age, the sex, the time of running 1600m and the instant heart rate after running; obtaining the subject's sex information at the same time; and performing standard conversion of the sex, the age, the time of running 1600m and the instant heat rate after running to take as parameters, inputting the maximum oxygen uptake BP neural network, and measuring the subject's maximum oxygen uptake, wherein the maximum oxygen uptake BP neural network is provided with an input layer, an output layer and one hiding layer, the input is provided with 5 input nerve cells, the hiding layer is provided with 11 nerve cells, and the output layer is provided with one nerve cell. The human body maximum oxygen uptake evaluation method can rapidly obtain the accurate maximum oxygen uptake result with no need for expensive device investment and is suitable for population cardiopulmonary function analysis in a large sample size.

Description

technical field [0001] The invention relates to the technical field of human body constitution detection, in particular to a method for evaluating human cardiopulmonary function, more specifically to a method for evaluating human body maximum oxygen uptake, and its application in human body cardiopulmonary function evaluation. Background technique [0002] Cardiorespiratory fitness is an important part of physical fitness and is related to large muscle groups, dynamics, and the ability to exercise at moderate to vigorous intensity for a long time. It is generally believed that the risk of premature death is higher if the cardiorespiratory function is too low, especially in terms of cardiovascular disease, and improving the level of cardiorespiratory fitness can reduce the risk of disease and mortality from many diseases. The best index for evaluating cardiopulmonary function is the maximum oxygen uptake, which is considered in the ACSM exercise test and exercise prescription...

Claims

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Application Information

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IPC IPC(8): G06N3/08
CPCG06N3/084
Inventor 王伟
Owner 王伟
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