Modeling, Control, and Clinical Validation of an Upper-Limb Medical Education Task Trainer for Elbow Spasticity and Rigidity Assessment

The goal of this study was to validate a series elastic actuator (SEA)-based robotic arm that can mimic three abnormal muscle behaviors, namely lead-pipe rigidity, cogwheel rigidity, and spasticity for medical education training purposes. Key characteristics of each muscle behavior were first modeled mathematically based on clinically-observed data across severity levels. A controller that incorporated feedback, feedforward, and disturbance observer schemes was implemented to deliver haptic target muscle resistive torques to the trainee during passive stretch assessments of the robotic arm. A series of benchtop tests across all behaviors and severity levels were conducted to validate the torque estimation accuracy of the custom SEA (RMSE: similar to 0.16 Nm) and the torque tracking performance of the controller (torque error percentage: < 2.8 %). A clinical validation study was performed with seven experienced clinicians to collect feedback on the task trainer's simulation realism via a Classification Test and a Disclosed Test. In the Classification Test, subjects were able to classify different muscle behaviors with a mean accuracy > 87 % and could further distinguish severity level within each behavior satisfactorily. In the Disclosed Test, subjects generally agreed with the simulation realism and provided suggestions on haptic behaviors for future iterations. Overall, subjects scored 4.9 out of 5 for the potential usefulness of this device as a medical education tool for students to learn spasticity and rigidity assessment.

Automated summary

The study aimed to validate a robotic arm based on a series elastic actuator (SEA) that can mimic three abnormal muscle behaviors for medical education training. Mathematical models of each behavior were created based on clinically-observed data. A controller incorporating feedback, feedforward, and disturbance observer schemes was implemented to deliver target muscle resistive torques. Benchtop tests and a clinical validation study were conducted to validate the accuracy of the torque estimation and the realism of the simulation. Results showed high accuracy and realism, indicating the potential usefulness of the device as a medical education tool.