Orthopedic Device Adjustment Using Patient Data and Expert Models
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Solution Overview
Problem
The adjustment of microprocessor-controlled orthopedic devices is time-consuming and costly, particularly for orthopedic technicians with little experience, relying heavily on iterative processes and patient feedback.
Innovation Solution
A method utilizing a digital communication link to an adjustment database, where adjustment values and patient data are stored, allowing for the calculation and display of optimal adjustment values on a mobile terminal device, enabling efficient and precise adjustment of orthopedic devices based on stored experience and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If iterative adjustment processes with patient feedback are used, then adjustment precision can be improved, but adjustment time and cost increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-calculating optimal adjustment values using machine learning models before actual device adjustment. The adjustment database stores pre-computed optimal parameters based on patient data, eliminating the need for time-consuming iterative adjustments during clinical practice.
Solution Approach 2:
The invention creates a digital copy of expert adjustment knowledge through machine learning models trained on data from experienced orthopedic technicians. These models replicate expert decision-making patterns, allowing less experienced technicians to achieve expert-level adjustment precision without requiring extensive training or iterative trial-and-error processes.
2Manufacturing precision
If iterative adjustment processes are used, then adjustment precision can be improved, but adjustment cost increases
Solution Approach 1:
The system copies expert knowledge into machine learning models that can be deployed at low marginal cost. Once trained on data from experienced technicians, these models provide expert-level adjustment recommendations to any user without requiring additional expert time or resources, significantly reducing adjustment costs while maintaining high precision.
Solution Approach 2:
The adjustment database and machine learning models enable self-service adjustment capabilities. Technicians can independently determine optimal adjustment values using the system without requiring repeated consultations with experienced experts or multiple adjustment sessions, reducing both time and cost while achieving precise adjustments.
3Manufacturing precision
If experience-based iterative adjustment is used, then adjustment quality can be improved, but device complexity increases
Solution Approach 1:
The invention extracts the complex decision-making logic from human experts and isolates it into machine learning models and adjustment databases. This separates the intellectual complexity from the operational process, allowing technicians to use simple queries and receive complex optimized recommendations without needing to understand or perform complex iterative adjustment procedures.
Data Source
AI summary
The invention relates to a method for adjusting a microprocessor-controlled orthopedic device which is worn on the body of a patient fitted with such a device and influences movement by microprocessor-controlled actuation of actuators, the method comprising the following computer-implemented steps:providing a digital communication link from a mobile terminal device to an adjustment database, in which at least one adjustment value for at least one parameter of the respective microprocessor-controlled actuation and associated patient data of a patient fitted with the respective orthopedic device are stored for a plurality of microprocessor-controlled orthopedic devices,calculating at least one adjustment value of at least one parameter of the microprocessor-controlled actuation of the orthopedic device of the patient depending on patient data from the patient whose microprocessor-controlled orthopedic device is to be adjusted, and/or the adjustment values stored in the adjustment database and associated patient data,displaying the at least one calculated adjustment value on the mobile terminal device in order to adjust the microprocessor-controlled orthopedic device.