Biological Extraction Classification for Personalized Physical Guidance
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Solution Overview
Problem
Existing systems fail to effectively assist individuals in maintaining or achieving an acceptable physical status, particularly for the elderly, obese, and infirm, who are at risk of frailty and dependency, by providing personalized guidance based on biological extraction data.
Innovation Solution
A computing device equipped with a parameter classifier that classifies biological extraction data into nutrition, endurance, and strength parameters, using machine-learning models, to determine a subject's physical status and generate personalized guidance for improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a system uses machine-learning models to classify biological extraction data into physiological parameters, then the accuracy and personalization of physical status determination is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The system segments the complex task of physical status determination into distinct physiological parameter categories (nutrition, endurance, strength). Each category is assessed through specific biological extraction data types, allowing the machine-learning model to process complex data in organized, manageable segments while maintaining high accuracy.
Solution Approach 2:
The patent introduces an intermediary processing layer that transforms raw biological extraction data into classified physiological parameters before final physical status determination. This intermediary classification system simplifies the overall complexity by creating structured intermediate representations that bridge raw data and final conclusions.
2Adaptability or versatility
If the system collects and analyzes multiple types of biological extraction data to generate comprehensive physiological parameters, then the personalization and effectiveness of physical guidance is improved, but the quantity of data processing and time required increase
Solution Approach 1:
The system performs preliminary classification of biological extraction data into predefined physiological parameter categories before comprehensive analysis. By pre-organizing data into nutrition, endurance, and strength parameters, the system reduces subsequent processing time while maintaining the ability to provide personalized physical guidance based on all collected data.
Data Source
AI summary
A system for determining a physical status of a subject, the system including a computing device configured to store a parameter classifier, the parameter classifier configured to classify biological extractions to physiological status parameters of subjects wherein the physiological status parameters include a nutrition parameter, an endurance parameter, and a strength parameter, receive biological extraction data of a subject, classify subject biological extraction to subject physiological parameters as a function of the stored parameter classifier, assign values to subject physiological status parameters as a function of the biological extraction data, indicate the physical status of the subject as a function of the subject physiological parameters, generate a physical guidance for the subject as a function of the physical status, and output the physical guidance.