<p>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: ~ 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 (CT) and a Disclosed Assessment Test (DAT). In the CT, 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 DAT, 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.</p>
<p>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: ~ 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 (CT) and a Disclosed Assessment Test (DAT). In the CT, 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 DAT, 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.</p>
<p>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: ~ 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 (CT) and a Disclosed Assessment Test (DAT). In the CT, 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 DAT, 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.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.