Fall Risk Factor Estimation via Walking Parameter Segmentation
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Solution Overview
Problem
Existing methods for evaluating fall risk, such as those described in PTL 1, do not provide clear factors for reducing fall risk, making it difficult for caregivers to suggest effective interventions for individuals with identified fall risk.
Innovation Solution
A factor estimation system that calculates walking parameters from body motion data during walking and estimates the main components of fall risk, allowing for the identification of specific factors contributing to fall risk, enabling targeted interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional fall risk evaluation methods are used, then fall risk can be evaluated, but the specific factors contributing to fall risk remain unknown
Solution Approach 1:
The patent segments the fall risk assessment into multiple independent components: muscle strength, muscle mass, balance, and cognitive function. Each component is evaluated separately through specific tests and measurements, allowing the system to identify which specific factor contributes most to fall risk. This segmentation enables targeted interventions for each identified factor rather than treating fall risk as a monolithic concept.
Solution Approach 2:
The patent introduces walking parameters as intermediary measurements that indirectly reflect the underlying fall risk factors. By measuring objective walking parameters (such as gait speed, step length, and body motion characteristics) and correlating them with the four main components, the system creates a bridge between observable behavior and underlying physiological/cognitive factors, enabling non-invasive assessment of multiple risk factors simultaneously.
2Measurement precision
If multiple assessment tests are administered to identify fall risk factors, then factor identification improves, but assessment time and complexity increase
Solution Approach 1:
The patent designs a comprehensive assessment system where a single set of walking parameter measurements serves multiple functions: it simultaneously evaluates muscle strength, muscle mass, balance, and cognitive function by analyzing different aspects of gait behavior. This multi-functional approach allows the system to identify all four fall risk factors through one integrated assessment rather than requiring separate tests for each factor, significantly reducing total assessment time while maintaining comprehensive factor identification.
Data Source
AI summary
A factor estimation system is a factor estimation system that estimates a factor of fall risk indicating a possibility of a fall of a measured person, including: a calculator that obtains body motion data indicating body motion of the measured person during walking, and calculates two or more walking parameters of the measured person based on the body motion data obtained; and a factor analyzer that estimates, based on the two or more walking parameters, one or more main components that are included in the factor of the fall risk of the measured person and are based on the two or more walking parameters, and outputs an estimation result.