Rehabilitation Robot Force Control Without EMG Sensors
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Solution Overview
Problem
Existing extremity rehabilitation devices lack adaptive force control mechanisms that do not require additional sensors like EMG, leading to increased complexity and cost, and offer limited user autonomy in trajectory following or resistance modes.
Innovation Solution
A robotic device with a single force sensor and processing unit that decomposes external forces into tangential and radial components, dynamically adjusting force assistance or resistance based on real-time feedback, allowing users to select rehabilitation trajectories and modes without additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional sensors like EMG sensors are integrated to achieve adaptive force control, then rehabilitation effectiveness is improved, but device complexity increases
Solution Approach 1:
The patent extracts and eliminates the need for additional EMG sensors by using only the force sensor that is already integrated into the robotic device. The control method processes force data from the single force sensor to generate adaptive force commands, thereby achieving rehabilitation effectiveness without adding device complexity through additional sensors.
Solution Approach 2:
The force sensor serves multiple functions: it detects user exertion force, determines trajectory deviation, and provides input for adaptive force control. This multi-functionality eliminates the need for separate EMG sensors while maintaining comprehensive monitoring and control capabilities for effective rehabilitation.
2Measurement precision
If additional sensors like EMG sensors are integrated to achieve adaptive force control, then force control accuracy is improved, but manufacturing cost increases
Solution Approach 1:
The patent removes the requirement for expensive EMG sensors and achieves force control accuracy using only the force sensor data. The control method processes force magnitude and direction from the single force sensor to generate precise adaptive force commands, reducing manufacturing cost while maintaining measurement precision.
3Device complexity
If users are provided with predefined trajectories with fixed resistance levels, then device complexity is reduced, but user autonomy is limited
Solution Approach 1:
The patent implements dynamic resistance adjustment where the resistance level is not fixed but adapts in real-time based on user performance. The control unit continuously monitors force sensor data and automatically adjusts the resistance level according to the user's capability, providing autonomy without increasing device complexity.
Solution Approach 2:
The system uses feedback from the force sensor to dynamically adjust resistance levels. The force sensor detects user exertion, and this information feeds back to the control unit which automatically modifies the resistance level, enabling user autonomy through adaptive control without adding complex sensor systems.
4Adaptability or versatility
If users can operate the device without constraints in fully free-form mode, then user autonomy is improved, but rehabilitation effectiveness decreases
Solution Approach 1:
The patent implements dynamic trajectory adjustment where the rehabilitation trajectory is not rigidly predefined but adapts based on user capability. The control unit uses force sensor data to dynamically adjust the trajectory within reasonable bounds, providing user autonomy while maintaining rehabilitation effectiveness through adaptive constraint modification.
Solution Approach 2:
The force sensor provides continuous feedback on user exertion and trajectory adherence. The control unit processes this feedback to dynamically adjust trajectory constraints, allowing users greater autonomy when they demonstrate capability while maintaining rehabilitation effectiveness through real-time adaptive control.
Data Source
AI summary
Robotic device control for assisting a user in performing extremity rehabilitation is disclosed. A method controls a robotic device to assist extremity rehabilitation by: detecting, through a force sensor of a handle part of the robotic device that is coupled to an end effector of the robotic device for moving the end effector, an external force; decomposing the detected external force into a tangential force and a radial force; scaling, according to a distance between a current position of the handle part and a desired trajectory of the handle part, the radial force; calculating, based on a sum of the tangential force and the scaled radial force, a motor velocity for motors of the end effector; and providing a velocity instruction based on the calculated motor velocity for rotating the motors to move the end effector.