Machine Vision Hand Joint Range-of-Motion Assessment Without Contact
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing hand joint angle measurement methods, such as manual goniometers and wearable devices, suffer from inefficiencies, intra- and inter-rater reliability issues, and require physical contact, which can be problematic for individuals with injuries or dermatological conditions.
Innovation Solution
A machine vision-based method and system that captures prior-movement and post-movement images of the hand to determine joint range of motion using multiple cameras and a processor, processing these images to calculate key point positions without physical contact, enabling comprehensive and efficient hand function assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual goniometers or inclinometers are used to measure hand joint angles, then measurement can be performed, but the process is inefficient and expensive with poor intra- and inter-rater reliability
Solution Approach 1:
The patent replaces manual mechanical measurement tools (goniometers, inclinometers) with a machine vision-based system using cameras and image processing algorithms. The system captures images of the hand, automatically identifies joint positions and movement trajectories, and calculates range of motion without requiring manual manipulation of measurement instruments, thereby eliminating intra- and inter-rater reliability issues while improving efficiency
Solution Approach 2:
The system enables self-assessment by allowing subjects to perform hand movements naturally while the automated vision system captures and analyzes the movements. The subject simply needs to place their hand on the supporter and perform the required movements, with the system automatically processing the images to provide measurement results without requiring skilled measurers
2Extent of automation
If wearable devices are used to sense hand movement, then automated measurement is achieved, but physical contact with the finger is required which causes difficulties for individuals with injuries or dermatological conditions
Solution Approach 1:
The patent introduces an intermediary medium - a camera-based vision system - that enables automated measurement without direct physical contact. Instead of wearable devices that must touch the skin, the system captures images of the hand from a distance, processes these images to identify joint positions and movement trajectories, and calculates range of motion, thereby eliminating the physical contact barrier for individuals with injuries or dermatological conditions
Solution Approach 2:
The system replaces mechanical contact-based sensing with optical non-contact measurement. By using cameras to capture hand movements and image processing algorithms to analyze the movements, the system achieves automated measurement without requiring physical contact with the subject's skin, making it suitable for individuals with burns, wounds, lacerations, or dermatological conditions
3Object-affected harmful factors
If optical measurement systems are used for non-contact measurement, then physical contact is eliminated, but the system lacks versatility for various hand movements and comprehensive hand function assessment
Solution Approach 1:
The patent creates a universal measurement system that can assess multiple hand movements and joint angles through a single integrated vision-based platform. The system supports various hand movements including flexion, extension, abduction, adduction, and circumduction, and can measure range of motion for different hand joints (MCP, PIP, DIP joints). The system provides comprehensive hand function assessment capabilities while maintaining non-contact measurement, making it adaptable to various assessment scenarios
Data Source
AI summary
The present disclosure provides a machine vision-based method for determining a range of motion of a joint of a hand of a subject and a system for implementing the same. The provided method comprises: facilitating the subject to perform a hand movement at a preset position; capturing at least two prior-movement images of the hand when the hand is in a neutral posture before performing the hand movement; capturing at least two post-movement images of the hand when the hand is in an assessment posture after performing the hand movement; processing the captured prior-movement images to obtain a plurality of prior-movement key point positions; processing the captured post-movement images to obtain a plurality of post-movement key point positions; and calculating the range of motion of the joint based on the plurality of prior-movement key point positions and the plurality of post-movement key point positions.