饮食健康评估方法及系统、以及计算机设备
By using multi-objective optimization and reinforcement learning loops for population clusters and individuals, dietary assessment indicators are quantified as different class constraints to generate daily energy and single-meal reference values for people with high blood lipids. This solves the problem of ambiguous assessment results in existing systems and achieves accurate dietary health assessment and personalized recommendations.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- QUANZHOU INST OF INFORMATION ENG
- Filing Date
- 2026-02-25
- Publication Date
- 2026-07-17
AI Technical Summary
Existing dietary health assessment systems lack personalization and efficiency for people with high blood lipids. They are difficult to iteratively optimize based on real-time weight, blood lipids, and compliance feedback, resulting in ambiguous assessment results and making it difficult for users to quickly determine whether each meal meets the standards.
By using multi-objective optimization and reinforcement learning loops for population clusters and individuals, dietary assessment indicators are quantified as different types of constraints to generate daily energy and single-meal reference values applicable to high blood lipids, and precise suggestions are made in combination with user characteristic data.
It enables precise dietary assessment of people with high blood lipids at both the population and individual levels, generates quantitative deviation results and provides personalized adjustment suggestions, thereby improving the accuracy of the assessment and user compliance.
Smart Images
Figure CN121725993B_ABST