AI Joint Function Monitoring With Optical Angle Measurement
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Solution Overview
Problem
Existing joint function measurement technologies are cumbersome, potentially harmful due to electromagnetic waves, inefficient in data collection and utilization, and lack integrated data sharing and personalized healthcare services.
Innovation Solution
An AI-based joint function analyzing and monitoring device that integrates IT technologies for musculoskeletal disease prevention, provides accurate joint range measurement, data collection, and personalized healthcare services, including joint image analysis, symptom comparison, and data sharing across hospitals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are attached to measure joint angles, then measurement precision is improved, but device complexity and ease of operation deteriorate due to cumbersome sensor attachment
Solution Approach 1:
The patent replaces the mechanical sensor attachment system with an optical imaging system. Instead of using physical sensors that require attachment to the patient's body, the system uses a camera to capture images and AI algorithms to calculate joint angles from the images. This substitution eliminates the need for physical sensor attachment while maintaining measurement capability.
Solution Approach 2:
The patent creates a digital copy of the patient's joint position through imaging. Rather than physically measuring with sensors, the system captures visual information through camera images and processes these images to derive joint angle data. This copying approach allows non-contact measurement while preserving measurement accuracy.
2Measurement precision
If Bluetooth sensors are used for joint measurement, then measurement capability is improved, but harmful factors increase due to electromagnetic waves
Solution Approach 1:
The patent replaces the electromagnetic-based Bluetooth sensor system with an optical imaging system. The camera-based approach uses light (optical energy) instead of radio waves (electromagnetic energy), thereby eliminating the harmful electromagnetic radiation while maintaining the ability to measure joint angles through image processing.
3Loss of information
If manual data transfer from A4 paper to EMR system is used, then data collection is achieved, but productivity deteriorates due to inefficient manpower utilization
Solution Approach 1:
The patent implements an automated system where the measurement device itself performs data collection, processing, and transmission to the EMR system. The device automatically captures images, calculates joint angles using AI algorithms, and transmits results electronically without requiring manual data entry by staff. This self-service approach eliminates the manual paper-to-digital transfer process.
Solution Approach 2:
The patent replaces the manual mechanical process of writing on A4 paper and physically transferring data with an automated digital system. The measurement device directly generates and transmits digital data to the EMR system through communication interfaces, eliminating the need for manual documentation and data entry processes.
4Loss of information
If data collection is performed at each hospital independently, then local data availability is improved, but loss of information increases due to scattered data that prevents big data collection
Solution Approach 1:
The patent implements a universal data format and communication interface that allows the measurement device to work with multiple hospital EMR systems. The device collects data in a standardized format that can be transmitted to and integrated with different hospital systems, enabling both local data availability and centralized big data collection across multiple institutions.
Solution Approach 2:
The patent introduces a standardized data transmission interface as an intermediary between the measurement device and various hospital EMR systems. This intermediary layer enables seamless data exchange between different systems, allowing data to be collected locally at each hospital while also being aggregated into a centralized database for big data analysis.
Data Source
AI summary
The present disclosure relates to an AI-based joint function analyzing and monitoring device that provides a life-cycle health management service for a user by converging IT technologies for the prevention and management of musculoskeletal diseases, provides a comparison analysis of the user's current joint status and symptom similarity with those with diseases by using only data of patients with diseases diagnosed by professors at tertiary university hospitals without image analysis results such as X-rays and MRIs, and operates as an auxiliary tool for doctors to diagnose diseases.