Gait Waveform Estimation Using User Attributes and Swing-Phase Features
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Solution Overview
Problem
Existing methods for estimating physical conditions based on gait analysis are limited by the need for expert interpretation, lack of accurate determination across attributes like gender and age, and inability to analyze swing phase features, and require multiple-direction imaging for analysis.
Innovation Solution
An estimation device that extracts feature amounts from gait waveforms using sensor data, specifically acceleration and angular velocity, to estimate physical conditions like pronation/supination based on attributes such as gender and age, using inference models tailored for different gait phases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If intensity metrics are calculated using motion sensor data, then gait analysis capability is improved, but expert determination is still required which reduces automation
Solution Approach 1:
The patent introduces an automated determination unit that acts as an intermediary between the intensity metric calculation and the final gait determination. This unit automatically compares calculated metrics against reference values and databases to determine gait characteristics without requiring expert intervention, thereby achieving both accurate measurement and automation
Solution Approach 2:
The patent replaces the manual expert determination process with an automated computational system. The determination unit uses algorithms to automatically analyze intensity metrics, compare them with reference data, and generate gait determinations, substituting the mechanical/expert process with an automated information processing system
2Measurement precision
If plantar pressure data is used for foot abnormality evaluation, then foot condition analysis is improved, but swing phase features cannot be extracted
Solution Approach 1:
The patent merges multiple data sources - combining plantar pressure sensor data with motion sensor data - to create a comprehensive gait analysis system. This combination allows the system to capture both stance phase information from pressure sensors and swing phase information from motion sensors, eliminating the limitation of using only one data source
3Ease of operation
If determination is made without considering user attributes, then processing simplicity is improved, but determination accuracy for pronation/supination decreases
Solution Approach 1:
The patent implements a dynamic determination process that adapts to individual users. The system automatically identifies relevant attributes for each user and dynamically adjusts the determination criteria and reference values accordingly. This allows the system to maintain simplicity in operation while achieving high accuracy by customizing the analysis to each user's characteristics
Solution Approach 2:
The patent changes determination parameters based on user attributes. The system modifies reference values, comparison thresholds, and analysis criteria according to detected user characteristics such as age, gender, and gait patterns. This parameter adaptation enables accurate determination for diverse users without requiring complex manual configuration
4Measurement precision
If multiple-direction imaging is used for gait analysis, then analysis comprehensiveness is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex multiple-direction imaging systems with simpler sensor-based measurement systems. Instead of using multiple cameras and image processing equipment, the system uses wearable motion sensors and plantar pressure sensors to directly measure gait parameters, achieving comprehensive analysis with reduced device complexity
Solution Approach 2:
The patent introduces sensor devices as intermediaries that directly capture gait information without requiring visual imaging. The motion sensors and pressure sensors act as intermediaries between the user's body movements and the analysis system, providing direct measurement data that eliminates the need for complex imaging and image processing infrastructure
Data Source
AI summary
An estimation device including a feature amount extraction unit that extracts, from a gait waveform extracted from time series data of sensor data based on a motion of a foot of a user, a feature amount according to an attribute of the user in a section in which a feature of a physical condition according to the attribute of the user appears; and estimates the physical condition of the user using the feature amount extracted according to the attribute of the user.