Novel Physical Fitness Fuzzy Evaluation Model for Individual Health Promotion

Area of Science:

• Preventive Medicine
• Health Promotion
• Biostatistics

Background:

• Physical fitness is crucial for health promotion and preventive medicine.
• Key indicators include cardiorespiratory endurance, muscular endurance, muscle power, and flexibility.
• Existing evaluation methods often rely on statistical inference and may not be optimal for small datasets.

Purpose of the Study:

• To propose an evaluation and analysis model for individual physical fitness suitable for small sample datasets.
• To develop a method that reduces misjudgment risks associated with sampling error.
• To create a user-friendly interface for monitoring multiple physical fitness indicators.

Main Methods:

• Utilized a fuzzy evaluation method, which is effective for small sample datasets.
• Developed an evaluation model based on the upper confidence limit of physical fitness indices.
• Created a simple and easy-to-use fuzzy evaluation form as an interface.

Main Results:

• The proposed model effectively evaluates individual physical fitness using small datasets.
• The upper confidence limit approach minimizes misjudgment risks from sampling errors.
• The fuzzy evaluation form provides a clear overview and convenient management of multiple indicators.

Conclusions:

• The fuzzy evaluation model offers a practical solution for individual physical fitness assessment.
• It enables simultaneous monitoring of multiple physical fitness indicators for health requirements.
• This approach supports individuals in maintaining healthy physical fitness levels.