Leg Muscle Strength Estimation via Walking Image Analysis
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Solution Overview
Problem
There is a need for a method to estimate leg muscle strength without requiring direct contact with the user, as some individuals find wearing health monitoring devices annoying and inconvenient.
Innovation Solution
A leg muscle strength estimation system that uses a camera to capture images of a user walking, processing the images to estimate muscle strength based on knee flexion angle and walking speed, without the user's awareness or intervention, utilizing a combination of two-dimensional and three-dimensional skeletal models and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wearable devices are used to monitor health, then measurement precision is improved, but ease of operation deteriorates due to the annoyance of wearing devices at all times
Solution Approach 1:
The patent replaces the mechanical wearable device system with an optical imaging system. Instead of using accelerometers, gyroscopes, and other mechanical sensors worn on the body, the invention uses a camera to capture images and estimates muscle strength through image processing and skeletal model analysis, thereby eliminating the need for physical contact with the user.
Solution Approach 2:
The patent creates a virtual copy of the user's skeletal structure through image processing. By capturing images and generating two-dimensional and three-dimensional skeletal models, the system replicates the user's physical state without requiring physical sensors on the body, enabling non-contact measurement of muscle strength.
2Ease of operation
If contactless measurement is implemented, then ease of operation is improved, but measurement precision may deteriorate
Solution Approach 1:
The patent transitions from two-dimensional image data to three-dimensional skeletal models to improve measurement precision. By constructing 3D skeletal models from 2D images and analyzing spatial relationships in multiple dimensions, the system achieves accurate muscle strength estimation without physical contact with the user.
Solution Approach 2:
The patent performs preliminary processing of images to extract skeletal information and construct skeletal models before actual muscle strength estimation. This preliminary action of creating accurate skeletal representations enables precise measurement during the actual assessment phase without requiring contact during measurement.
Data Source
AI summary
A leg muscle strength estimation system includes: an obtainer that obtains an image including a user that is walking as a subject of the image; and an estimator that estimates a leg muscle strength of the user based on the obtained image.