Cognitive Function Evaluation via Ankle and Knee Joint Angles
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Solution Overview
Problem
Current technologies for evaluating cognitive function based on walking motion are not easily and highly accurate, requiring complex setups and relying on limited parameters, which hinders effective assessment of cognitive decline.
Innovation Solution
A cognitive function evaluation method that detects and uses the angles of the ankle and knee joints from walking data, combined with machine learning models to determine cognitive function levels, allowing for precise evaluation without the need for large-scale devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional walking parameter measurement methods are used, then cognitive function evaluation can be performed, but the evaluation accuracy is insufficient and the system complexity increases
Solution Approach 1:
The patent replaces complex mechanical measurement systems with image processing technology. Instead of using sophisticated motion capture equipment or force plates, the system uses standard cameras to capture walking images and extracts joint angle information through image analysis algorithms, thereby reducing device complexity while maintaining or improving measurement precision
Solution Approach 2:
The patent introduces an intermediary processing layer between simple image capture and cognitive function evaluation. Image processing algorithms serve as intermediaries that extract meaningful joint angle parameters from raw images, which then feed into the cognitive function evaluation model, enabling accurate assessment without requiring complex direct measurement devices
2Measurement precision
If limited walking parameters are used, then the evaluation system remains simple, but the cognitive function evaluation accuracy is insufficient
Solution Approach 1:
The patent segments the walking motion into specific anatomical components by extracting joint angles (ankle, knee, hip) as independent parameters. This segmentation allows the system to focus on specific biomechanical features that are most relevant to cognitive function, improving evaluation accuracy without requiring measurement of all possible walking parameters
Solution Approach 2:
The patent transforms raw image data into meaningful biomechanical parameters (joint angles) through image processing. By changing the parameter representation from pixel coordinates to anatomical joint angles, the system achieves higher evaluation accuracy while the automated image processing reduces the difficulty of parameter detection
3Measurement precision
If large-scale measurement devices are used, then measurement accuracy improves, but the ease of operation and deployment decreases
Solution Approach 1:
The patent replaces large-scale mechanical measurement devices with lightweight image processing systems. Standard cameras and computational algorithms substitute for complex mechanical apparatus, maintaining measurement precision while dramatically improving ease of operation and deployment in various settings
Solution Approach 2:
The patent creates a visual copy of the walking motion through image capture and processing. Instead of requiring physical interaction with complex measurement devices, the system captures optical information and processes it computationally, making the system easier to operate while achieving accurate parameter extraction
Data Source
AI summary
A cognitive function evaluation method in a cognitive function evaluation device that evaluates a cognitive function based on a walking motion of a subject includes: acquiring walking data related to walking of the subject; detecting, from the walking data, at least one of an angle of an ankle joint of one foot and an angle of a knee joint of one leg of the subject; and determining a cognitive function level of the subject using at least one of the angle of the ankle joint and the angle of the knee joint.