AI System for Mitigating Nutrient Gaps in Alternate Day Fasting
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Solution Overview
Problem
Individuals following Alternate Day Fasting regimens face challenges in identifying and mitigating nutrient inadequacies due to variability in real-life eating patterns and lack of access to nutritional databases and expertise, leading to potential health risks.
Innovation Solution
An AI-based system that identifies and quantifies nutritional inadequacies by simulating dietary intakes based on personal characteristics and dietary rules, providing personalized dietary recommendations and lifestyle guidance to mitigate nutrient gaps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If individuals follow Alternate Day Fasting regimens to achieve weight loss and health benefits, then weight management and health parameters improve, but nutrient intake adequacy deteriorates
Solution Approach 1:
The patent performs preliminary identification and quantification of nutrient inadequacies before they become severe health problems. The AI-based system analyzes dietary patterns and predicts nutrient gaps in advance, allowing individuals to take corrective actions proactively rather than reactively.
Solution Approach 2:
The system implements continuous feedback by monitoring dietary intake, comparing it against nutritional requirements, and providing real-time recommendations. This closed-loop approach ensures that nutrient inadequacies are detected and corrected ongoing, maintaining both weight loss benefits and nutritional adequacy.
2Ease of operation
If individuals attempt to self-monitor their nutrient intake without professional guidance, then autonomy and accessibility improve, but accuracy and reliability of nutritional assessment deteriorate
Solution Approach 1:
The patent enables individuals to independently assess and monitor their own nutritional status through an AI-based system that requires minimal user input. Users simply report their dietary choices, and the system automatically performs complex nutritional analysis, making professional-grade assessment accessible to everyone without requiring expertise.
Solution Approach 2:
The system replaces the need for manual nutritional analysis and expert interpretation with an AI-based computational approach. The AI algorithm automatically processes dietary data, calculates nutrient intakes, identifies inadequacies, and generates recommendations, substituting human expertise with automated intelligent systems that provide consistent and accurate results.
3Reliability
If clinical trials use controlled conditions and constant supervision to assess nutrient intake, then data reliability improves, but real-life applicability and external validity deteriorate
Solution Approach 1:
The system allows individuals to self-report their dietary intake in their natural home environment without researcher presence or controlled conditions. This self-service approach captures real-life eating behaviors while maintaining data reliability through automated AI analysis that objectively processes the reported information.
Solution Approach 2:
The AI-based system is designed to work across diverse populations, dietary patterns, and living conditions without requiring modification of the assessment protocol. It universally applies nutritional analysis algorithms to various ADF regimens and dietary preferences, making the system adaptable to real-life diversity while maintaining consistent assessment quality.
Data Source
AI summary
The present invention relates to novel nutritional compositions and methods to mitigate inadequate nutrient intakes of intermittent fasting (IF) diets, in particular alternate day fasting regimens (ADF). It also covers an Artificial Intelligence (AI)-based system for determination, quantification and mitigation of nutritional risks of said ADF diets in adults.