Gait-Based Care Estimation Using Wearable Sensor Features
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Solution Overview
Problem
Existing technologies are unable to accurately estimate care-related information, such as frailty and falling risk, based on a user's gait, particularly in general daily life scenarios without the need for motion capture devices.
Innovation Solution
An estimation device that acquires sensor data from a user's walking and physical data, using an estimation model to output care-related information like frailty probability, by extracting feature quantities from sensor and physical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion capture devices are used to measure gait data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex motion capture devices with simple wearable sensors (accelerometers, gyroscopes, magnetometers) that measure gait parameters. The mechanical measurement system is substituted with electronic sensing devices that can be integrated into footwear, dramatically reducing device complexity while maintaining measurement capability through signal processing and feature extraction algorithms
Solution Approach 2:
The patent introduces an intermediary processing system that includes a measurement value acquisition unit, feature quantity extraction unit, and estimation unit. This intermediary layer processes raw sensor data to extract meaningful gait features and estimates care-related information, bridging the gap between simple sensor measurements and clinical-grade assessment without requiring complex measurement equipment
2Measurement precision
If feature quantities are extracted from sensor data to estimate care-related information, then estimation accuracy is improved, but information processing complexity increases
Solution Approach 1:
The patent segments the gait analysis process into distinct functional units: a measurement value acquisition unit that collects sensor data, a feature quantity extraction unit that processes raw data into meaningful parameters, and an estimation unit that generates care-related information. This segmentation allows each unit to be optimized independently and simplifies the overall processing complexity through modular design
Solution Approach 2:
The patent extracts specific feature quantities from raw sensor data that are most relevant for estimating care-related information. By selectively extracting only the necessary features (such as gait speed, stride length, variability parameters) rather than processing all possible data, the system achieves high estimation accuracy while minimizing processing complexity
Data Source
AI summary
An estimation device that includes an acquisition unit that acquires sensor data measured in accordance with walking of the user, and physical data of the user, a storage unit that stores an estimation model and the physical data, the estimation model outputting care-related information in response to inputs of a feature quantity extracted from the sensor data and the physical data, an estimation unit that inputs the feature quantity extracted from the sensor data of the user and the physical data into the estimation model to estimate the care-related information of the user, and an output unit that outputs the estimated care-related information of the user.