Robotic Rehabilitation System Adaptive Treatment Control
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Solution Overview
Problem
Current robotic physical rehabilitation systems face challenges in providing versatile and efficient assessment and treatment for diverse diagnoses, such as stroke, spinal cord injury, and cerebral palsy, due to inadequate infrastructure and limited therapist oversight, necessitating a system that can analyze user interaction data to adapt treatment plans effectively.
Innovation Solution
A robotic rehabilitation system comprising robotic motion machines, sensors, and a control system that analyzes user interaction data to track past treatment and determine future actions, sending commands to adjust the system's feedback and interaction, enabling faster diagnosis and treatment planning, and allowing for competitive, collaborative, or cooperative play among users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic rehabilitation systems are used to reduce therapist oversight, then productivity increases, but measurement precision of user impairment deteriorates
Solution Approach 1:
The system continuously collects user interaction data from sensors during rehabilitation exercises and feeds this information back to the control system. The control system analyzes the data in real-time to adjust treatment parameters and provide immediate feedback to users through the robotic interface, enabling automated precision assessment without therapist oversight.
Solution Approach 2:
The patent replaces manual therapist assessment with an automated control system that uses sensors to detect user movements, forces, and interactions. The control system processes this data algorithmically to evaluate impairment levels, substituting human mechanical assessment with automated electronic measurement and analysis.
2Adaptability or versatility
If the system treats diverse diagnoses with single robotic platform, then adaptability improves, but device complexity increases
Solution Approach 1:
The robotic rehabilitation system is designed with universal end-effectors and interchangeable modules that can accommodate multiple diagnoses and treatment types. The control system includes pre-configured treatment protocols for various conditions (stroke, spinal cord injury, cerebral palsy) that can be selected and adapted through software, allowing a single physical platform to serve multiple therapeutic purposes.
Solution Approach 2:
The system employs dynamic configuration capabilities where treatment parameters, resistance levels, motion ranges, and exercise protocols can be adjusted in real-time based on the user's diagnosis and progress. The robotic interface can dynamically modify its mechanical properties through controlled impedance and adaptive stiffness to match different therapeutic requirements.
3Manufacturing precision
If user interaction data is analyzed to determine future treatment actions, then manufacturing precision of treatment planning improves, but loss of time in data processing increases
Solution Approach 1:
The control system pre-processes and stores user interaction data during each exercise session, organizing it into structured formats that facilitate rapid analysis. Treatment protocols and decision algorithms are pre-configured in the system, allowing the control system to quickly match analyzed data against predefined criteria and generate treatment recommendations without extensive real-time computation.
Data Source
AI summary
Methods, systems, and computer readable media for analyzing robotic physical rehabilitation systems. In some examples, a method includes receiving user interaction data characterizing a user's interaction with a robotic rehabilitation system. The robotic rehabilitation system includes one or more robotic motion machines, a control system for controlling motors of the robotic motion machines, and one or more sensors for collecting the user interaction data while the user performs physical rehabilitation training using the one or more robotic motion machines. The method includes analyzing the user interaction data to track the user's past course of treatment and determine an action for the user's future course of treatment. The method includes sending one or more commands to the control system of the robotic rehabilitation system based on the action for the user's future course of treatment.