Orthopedic Force Adjustment Using Patient Comfort Feedback
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Solution Overview
Problem
Existing treatment apparatuses lack the ability to adapt to individual patient comfort levels during rehabilitation, leading to suboptimal treatment efficacy and patient discomfort.
Innovation Solution
A system that includes a clinician interface for creating treatment plans, a patient interface for real-time feedback, and a treatment apparatus that adjusts based on patient comfort levels, using sensors to measure position and force, and machine learning models to optimize treatment protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If treatment apparatus uses fixed treatment protocols, then device complexity is reduced, but adaptability to individual patient comfort levels deteriorates
Solution Approach 1:
The system implements real-time feedback loops where patient responses (comfort level, pain level, adherence indicators) are continuously collected via sensors and user interface, processed by control algorithms, and used to dynamically adjust treatment parameters. This closed-loop feedback mechanism enables the apparatus to adapt to individual patient needs without requiring overly complex manual configuration.
Solution Approach 2:
The treatment protocol transitions from a static, pre-programmed sequence to a dynamic, real-time adjustable regimen. Treatment parameters such as force magnitude, exercise duration, resistance levels, and session frequency are continuously modified based on real-time patient feedback and adherence data, allowing the system to evolve during each treatment session and across multiple sessions.
2Reliability
If treatment apparatus monitors real-time patient feedback, then treatment effectiveness is improved, but device complexity increases
Solution Approach 1:
The control system integrates multiple functions into a unified platform: it monitors physiological parameters via sensors, collects subjective feedback through the user interface, processes adherence data, executes treatment protocols, and adjusts parameters in real-time. This multi-functional integration reduces the need for separate specialized systems while maintaining comprehensive monitoring and control capabilities.
Solution Approach 2:
The system automatically processes patient feedback and adherence data through embedded algorithms, making real-time adjustments to treatment parameters without requiring constant clinician intervention. The apparatus self-regulates within predefined safety boundaries, reducing the operational burden on healthcare providers while maintaining treatment effectiveness.
3Ease of operation
If treatment apparatus provides personalized adjustments, then patient comfort is improved, but adherence monitoring complexity increases
Solution Approach 1:
The system combines comfort adjustment mechanisms with adherence monitoring into a unified control framework. Patient feedback on comfort levels is collected through the same interface used for adherence tracking, and both data streams are processed together to generate personalized treatment adjustments. This merging eliminates the need for separate monitoring systems and simplifies the overall architecture.
Data Source
AI summary
In one embodiment, a method is disclosed. The method includes controlling, by one or more processing devices and using a target force setting value to be exerted by a body part of the patient, an electromechanical machine comprising an actuator configured to produce an external force based on the target force setting value. The method includes causing, via the one or more processing devices, presentation of a first user interface on a patient interface. The first user interface comprises an adjustment confirmation screen that solicits a response regarding the patient's comfort level with the target force setting value. The method includes changing, based on the response, the target force setting value, and controlling the actuator to produce an external force based on the changed target force setting value.