Name
Title | ||
|---|---|---|
Development of a Series Elastic Elbow Neurological Exam Training Simulator for Lead-pipe Rigidity |
Abstract | ||
|---|---|---|
This paper describes the development of a 1-DOF kinesthetic force display device in the form of an arm training simulator that replicates the haptic feeling of lead-pipe rigidity in the elbow joint. Patients with lead-pipe rigidity have uniformly elevated muscle tone throughout the range of motion, which is an important clinical sign for diagnosing Parkinson's disease during a neurological examination. The simulator could provide training opportunities for healthcare trainees to learn and practice the assessment technique for lead-pipe rigidity. The simulator was driven by a series elastic actuator in order to have more accurate joint torque control in a safe and cost-effective manner for rendering abnormal muscle resistance. A mathematical model of lead-pipe rigidity based on hyperbolic tangent was proposed to recreate the elevated muscle resistance at different Unified Parkinson's Disease Rating Scale (UPDRS) 0-3. Performance of the simulator was evaluated through benchtop tests and rigidity simulation tests. Preliminary results suggested the simulator had good torque control accuracy (an average RMSE < 0.27 Km) and good fidelity in mimicking clinically-measured lead-pipe rigidity at UPDRS 0-3. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICRA48506.2021.9560891 | 2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021) |
DocType | Volume | Issue |
Conference | 2021 | 1 |
ISSN | Citations | PageRank |
1050-4729 | 0 | 0.34 |
References | Authors | |
1 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kevin G. Gim | 1 | 0 | 0.68 |
| Maxine He | 2 | 0 | 0.34 |
| Mahshid Mansouri | 3 | 0 | 0.34 |
| Yinan Pei | 4 | 0 | 0.34 |
| Evan Ripperger | 5 | 0 | 0.34 |
| Christopher M. Zallek | 6 | 0 | 0.68 |
| Elizabeth T. Hsiao-Wecksler | 7 | 10 | 3.24 |