Pelvic Inclination Estimation via Foot Sensor Gait Features
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Solution Overview
Problem
Existing methods for estimating pelvic inclination, an index related to waist movement, face challenges in accuracy due to sensor placement limitations and the need for additional equipment like cameras, limiting their usability in daily life.
Innovation Solution
A device and method that utilize sensor data from foot movement to estimate pelvic inclination by acquiring feature amounts from spatial acceleration and angular velocity, using an estimation model to output accurate pelvic inclination values, allowing for high-accuracy estimation without the need for additional equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an acceleration sensor is attached to the waist to measure pelvic inclination, then the measurement can be performed, but the sensor placement limits free actions and measurement accuracy decreases if the position deviates
Solution Approach 1:
The patent uses sensor data from the foot (which is easier to attach and remains in a consistent position) to create a computational model that copies or estimates the pelvic inclination measurements that would be obtained from a waist-mounted sensor. This allows indirect measurement of pelvic inclination through foot sensor data processing, avoiding the need for direct waist sensor attachment.
Solution Approach 2:
The patent introduces an estimation model as an intermediary between the foot sensor data and the pelvic inclination measurement. The model processes gait waveform features from foot sensors to infer pelvic inclination, serving as a mediator that translates easily-obtainable foot movement data into accurate pelvic inclination estimates without requiring direct waist sensor attachment.
2Measurement precision
If a camera is used to photograph walking movement to analyze pelvic inclination, then walking characteristics can be captured, but additional equipment is required which reduces usability in daily life
Solution Approach 1:
The patent replaces the camera-based optical measurement system with a computational model that processes sensor data to copy the essential gait characteristics needed for pelvic inclination estimation. Instead of capturing visual images of walking movement, the system uses acceleration and angular velocity sensor data to infer the same biomechanical information through signal processing and machine learning.
Solution Approach 2:
The patent substitutes the mechanical/optical camera system with an electronic sensor-based system. Instead of using a camera to visually track and analyze walking movement, the invention uses acceleration sensors and angular velocity sensors combined with a computational estimation model to measure pelvic inclination, replacing complex optical machinery with simpler electronic sensing and processing.
3Device complexity
If sensor data from foot movement is used to estimate pelvic inclination, then additional equipment like cameras is not needed, but accurate estimation of waist movement index must be achieved indirectly
Solution Approach 1:
The patent introduces a sophisticated estimation model as an intermediary that processes multiple features from foot sensor data (gait waveform characteristics, acceleration patterns, angular velocity) to accurately infer pelvic inclination. This intermediary model bridges the gap between foot movement measurements and waist movement estimation, enabling accurate indirect measurement through complex computational processing.
Solution Approach 2:
The patent transforms the measurement approach by changing from direct waist sensor attachment to indirect foot-based estimation. It processes sensor data through multiple transformations: converting raw acceleration and angular velocity data into gait waveform features, extracting relevant parameters, and applying these transformed parameters in an estimation model to derive pelvic inclination with high accuracy despite the indirect measurement path.
Data Source
AI summary
Provided is a pelvic inclination estimation device including a communication unit that acquires feature amount data including a feature amount to be used for estimation of a pelvic inclination, the feature amount being extracted from a gait waveform of a spatial acceleration and a spatial angular velocity included in sensor data related to movement of a foot of a subject, a storage unit that stores an estimation model that outputs an estimation value related to the pelvic inclination according to an input of the feature amount included in the feature amount data, an estimation unit that inputs a feature amount included in the acquired feature amount data to the estimation model and estimate a pelvic inclination of the subject according to the estimation value output from the estimation model, and an output unit that outputs information associated to the pelvic inclination of the subject.