Exercise scheme generation system based on multi-information

Abstract

The invention discloses an exercise scheme generation system based on multi-information. The exercise scheme generation system is characterized by comprising a remote service platform, a health sign testing module, an exercise capacity testing module, an exercise target reasoning module and an intelligent fitness equipment module, wherein the remote service platform is composed of a questionnaire unit, an exercise target reasoning unit and an exercise scheme generation unit. The questionnaire unit is used for collecting user health information. The health sign testing module is used for collecting test index data of health signs of a user. The exercise capacity testing module is used for collecting the test index data of the exercise capacity of the user. The exercise target reasoning unit reasons according to the multi-information and obtains an exercise target of the user. The exercise target generation unit is used for generating an exercise scheme composed of sport events, exercise duration, exercise frequency, exercise intensity and whether medical supervision is required to be provided for the intelligent fitness equipment module for execution. The exercise scheme generation system can guide the user to perform scientific, coherent, systematic and safe fitness.

Description

technical field [0001] The invention relates to the field of sports and fitness, in particular to a multi-information-based exercise program generation system. Background technique [0002] With the improvement of national living standards and the rapid development of the economy, people are no longer concerned about basic necessities of life, but the demand for health and stress relief is also increasing. Health and decompression must be inseparable from exercise and fitness, and the field of exercise and fitness is also gradually increasing. develop. [0003] Although the fitness industry is gradually developing and nearly mature, there are still many problems, as follows: [0004] 1. Most of the current fitness centers focus on the training equipment, while ignoring the comprehensive detection of the user's health signs and exercise ability. The generation of exercise programs is also based on a popular guidance program on a certain training equipment. There are large l...

AI Technical Summary

Problems solved by technology

[0004] 1. Most of the current fitness centers focus on the training equipment, while ignoring the comprehensive detection of the user's health signs and exercise ability. The generation of exercise programs is also based on a popular guidance program on a certain training equipment. There are large loopholes in the exercise program with complete individual health information and fitness guidance, and there are invisible risks to the user's health, which can easily cause sports injuries

[0005] 2. The fitness guidance for users in fitness facilities mainly relies on the personal experience of fitness coaches, lacks long-term and systematic planning for users' exercise programs, and lacks scientific and coherent fitness guidance

[0006] 3. The management of users in fitness places is primitive and extensive, often only focusing on the number of workouts of users, and the fitness equipment in fitness places is relatively isolated, the user's exercise program lacks integrity and diversity, and there is a lack of overall and quantitative assessment of the amount of user fitness exercise , so it is difficult to evaluate the user's fitness effect, and the user himself lacks a macroscopic grasp of fitness

[0007] 4. Traditional fitness venues lack batch management of users’ health information. Fitness coaches mostly focus on body shaping and lack a comprehensive grasp of health knowledge. Therefore, it is impossible to generate scientific exercises for users with chronic diseases or disease history program, unable to give correct fitness guidance, and the risk of exercise is relatively high

[0008] 5. The intelligence of fitness equipment in traditional fitness places is low, which leads to the inability to quantify the generation and execution of exercise programs, making the exercise programs relatively rigid, lacking in fun and humanized services of human-computer interaction

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