Functional Age Indices Model Using Sensor Data
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Solution Overview
Problem
Conventional age-based decision-making methods fail to account for individual variations in health and disposition, leading to inadequate lifestyle recommendations as they solely rely on chronological age.
Innovation Solution
A method involving the collection of sensor data to construct a functional age indices model using machine learning, which determines physiological, psychological, and social age indices, enabling more personalized recommendations and dynamic adjustments based on feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If chronological age is used for decision-making, then simplicity and ease of operation are improved, but measurement precision and reliability are worsened
Solution Approach 1:
The patent transforms the single parameter of chronological age into multiple functional age parameters (physiological, psychological, social age indices) derived from sensor data. This allows the system to maintain ease of operation while significantly improving measurement precision by capturing individual variations in health and disposition that chronological age alone cannot reflect.
Solution Approach 2:
The patent introduces sensor data as an intermediary between chronological age and lifestyle recommendations. Sensors collect objective physiological, behavioral, and environmental data that serve as a mediator to determine functional age indices, thereby improving assessment accuracy without requiring complex manual evaluations.
2Measurement precision
If sensor data collection and machine learning modeling are implemented, then measurement precision and personalization are improved, but device complexity and data processing requirements are worsened
Solution Approach 1:
The patent employs a multi-functional machine learning model that simultaneously processes diverse sensor data types (physiological, behavioral, environmental) to generate multiple functional age indices (physiological, psychological, social). This universal approach improves measurement precision while managing device complexity by consolidating multiple functions into a single integrated system.
Solution Approach 2:
The system implements self-service mechanisms through automated sensor data collection, processing, and model updating. The machine learning model continuously learns from new data and adapts to individual users, reducing the need for manual intervention and complex external processing systems while maintaining high measurement precision.
3Adaptability or versatility
If functional age indices are used for recommendations, then adaptability and personalization are improved, but loss of time for data collection and processing is worsened
Solution Approach 1:
The patent performs preliminary actions by continuously collecting and preprocessing sensor data in the background, maintaining updated functional age indices ready for immediate application. This allows the system to provide personalized recommendations without requiring time-consuming data collection and processing at the moment of decision-making, thus improving adaptability while minimizing time loss.
Data Source
AI summary
An approach is described with respect to functional age analysis. A method pertaining to such approach may include receiving sensor data collected on a plurality of individuals via a plurality of sensor devices. The method further may include constructing an age indices model by applying machine learning to the collected sensor data. The method further may include determining one or more functional age indices for a subject individual by applying the age indices model to profile data associated with the subject individual. In an embodiment, the method further may include transmitting the one or more functional age indices determined for the subject individual to a professional or a knowledge base, and receiving and processing one or more prescribed recommendations for the subject individual. According to such embodiment, the method further may include updating the age indices model based upon feedback received with respect to the one or more prescribed recommendations.