Daily Activity Indexing for Frailty and Dementia Risk Assessment
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Solution Overview
Problem
Existing methods for predicting frailty or dementia based on daily activities are insufficient as they either focus on quantity or quality, failing to integrate both aspects effectively for prevention.
Innovation Solution
An information processing device and method that calculates an index integrating the quantity and quality of daily activities by classifying them into intellectually active and passive/physiological types, using weighted coefficients to evaluate diversity, and considering sedentary behavior interruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If daily activities are evaluated based on quantity only, then the evaluation is simple, but it is insufficient for preventing frailty or dementia
Solution Approach 1:
The patent segments daily activities into multiple dimensions: activity type (intellectually active vs. passive/physiological), frequency, and sedentary behavior characteristics. This segmentation allows comprehensive evaluation while maintaining systematic simplicity through structured categorization.
Solution Approach 2:
The patent introduces multiple parameters including activity type classification, frequency metrics, and sedentary behavior parameters with weight coefficients. These parameter changes transform a simple quantity-based evaluation into a multi-dimensional assessment that captures both quantity and quality aspects.
2Reliability
If daily activities are evaluated based on quality only, then the evaluation captures activity type, but it lacks comprehensive coverage of activity patterns
Solution Approach 1:
The patent merges quality assessment (activity type classification into intellectually active vs. passive/physiological) with quantity assessment (frequency counts and total time). This combination is achieved through a unified index calculation that integrates both dimensions with appropriate weight coefficients.
Solution Approach 2:
The patent adds frequency as a new dimension to the quality-based activity type classification. By incorporating frequency data and combining it with activity type through weighted calculation, the system achieves comprehensive coverage without losing the nuance of quality assessment.
3Reliability
If an integrated index is calculated using multiple parameters, then comprehensive evaluation is achieved, but the calculation complexity increases
Solution Approach 1:
The calculation system is segmented into distinct functional units: information acquisition unit for data collection, index calculation unit for computation, and separate handling of different activity types. This segmentation reduces complexity by organizing the multi-parameter calculation into manageable, modular components.
Solution Approach 2:
Different weight coefficients are assigned to different activity types (intellectually active vs. passive/physiological) based on their local importance for frailty and dementia prevention. This local quality approach allows the system to prioritize relevant activities while maintaining overall comprehensiveness.
4Measurement precision
If sedentary behavior is considered in detail, then the evaluation accuracy improves, but the data processing complexity increases
Solution Approach 1:
Sedentary behavior parameters are extracted as a distinct component from overall activity data. The system separately identifies and processes sedentary time, interruption frequency, and duration, then integrates these extracted parameters into the overall index calculation with appropriate weighting.
Solution Approach 2:
Weight coefficients serve as intermediaries between detailed sedentary behavior measurements and the overall evaluation index. These coefficients mediate the integration process, translating complex sedentary behavior data into meaningful contributions to the final assessment without requiring direct complex processing of all raw data.
Data Source
AI summary
An information processing device includes an information acquisition unit configured to acquire daily activity type information, which is information indicating a daily activity type that is a type of a daily activity of a user, and daily activity frequency information, which is information indicating the frequency of the daily activity for each daily activity type, and an index calculation unit configured to calculate an index related to the daily activity by using the frequency for each daily activity type and a weight coefficient set for each daily activity type, based on the daily activity type information and the daily activity frequency information acquired by the information acquisition unit.