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Non-contact physical fitness test system and method

A test system and non-contact technology, applied in neural learning methods, gymnastics equipment, character and pattern recognition, etc. to improve maintainability and portability, reduce interference, and enrich user information

Inactive Publication Date: 2022-02-08
BEIJING FORESTRY UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This technology helps people get their own exercise more easily while being able to track how well they are doing them over time or with less effort compared to traditional methods like running water tests that require equipment attached around an arm's shoulder.

Problems solved by technology

Technological Problem addressed by this patented technical problem described in the patents relates to improving exercise performance without causing issues like interference with wireless communication networks used during resistance training sessions due to environmental constraints.

Method used

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  • Non-contact physical fitness test system and method
  • Non-contact physical fitness test system and method
  • Non-contact physical fitness test system and method

Examples

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Embodiment 1

[0021] Such as figure 1 As shown, the embodiment of the present invention provides a kind of non-contact physical fitness testing system, comprises following module:

[0022] Physical fitness test control module 1: The user selects the sports mode, uploads or inputs sports video through the camera; according to the sports mode, uses the OpenPose framework to estimate the human body posture of the sports video, and obtains the coordinates of the key points of the human body; calculates the torso joints according to the coordinates of the key points of the human body Angle between;

[0023] Sit-ups test module 2: use the finite state machine as a calculation model for judging sit-ups, define the state of the tested human body during sit-ups as a finite state, and define the possible states of the tested human body during the sit-up process There are four types: "preparation state", "process state", "counting state" and "other states"; the state sequence defining a complete sit-...

Embodiment 2

[0056] Such as Figure 4 As shown, the embodiment of the present invention provides a non-contact physical fitness testing method, comprising the following steps:

[0057] Step S1: The user selects the video input method, wherein the video input method includes: uploading the motion video method and the camera acquisition motion video method, and using the physical fitness test control module to analyze the motion video to obtain the coordinates of the key points of the human body. Point coordinates calculate the angle between the joints of the trunk;

[0058] Step S2: The user selects the exercise mode, and calls the corresponding module to test the exercise, including:

[0059] Sit-ups test module: use the finite state machine as a calculation model for judging sit-ups, define the state of the tested human body in sit-ups as a finite state, and define the possible states of the tested human body in the process of completing sit-ups as Four types: "preparation state", "proc...

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Abstract

The invention relates to a non-contact physical fitness test system and method, and the system comprises a physical fitness test control module which is used for obtaining the coordinates of key points of a human body, and calculating the angle between each trunk joint, a sit-up testing module used for counting sit-ups, a push-up test module used for counting push-ups, a panel support test module used for counting panel supports, and a test feedback module used for feeding back the detection data to a user. According to the system provided by the invention, a human body posture recognition deep learning framework is utilized, skeleton coordinate information of a user is obtained on the premise that the user does not need to carry any instrument and equipment, accurate motion counting or timing is carried out, and the detection process does not need to be intervened by others. And meanwhile, by using a finite-state machine algorithm model, the measurement of motion data in the motion detection process is accurate, and the method has relatively good fault tolerance for other interference actions except for the tested action.

Description

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Claims

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Application Information

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Owner BEIJING FORESTRY UNIVERSITY
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