Learning Dynamic Patient-Robot Task Assignment and Scheduling for A Robotic Rehabilitation Gym.
IEEE Int Conf Rehabil Robot
; 2022: 1-6, 2022 07.
Article
en En
| MEDLINE
| ID: mdl-36176110
A robotic rehabilitation gym is a setup that allows multiple patients to exercise together using multiple robots. The effectiveness of training in such a group setting could be increased by dynamically assigning patients to specific robots. In this simulation study, we develop an automated system that dynamically makes patient-robot assignments based on measured patient performance to achieve optimal group rehabilitation outcome. To solve the dynamic assignment problem, we propose an approach that uses a neural network classifier to predict the assignment priority between two patients for a specific robot given their task success rate on that robot. The priority classifier is trained using assignment demonstrations provided by a domain expert. In the absence of real human data from a robotic gym, we develop a robotic gym simulator and create a synthetic dataset for training the classifier. The simulation results show that our approach makes effective assignments that yield comparable patient training outcomes to those obtained by the domain expert.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Robótica
/
Procedimientos Quirúrgicos Robotizados
/
Rehabilitación de Accidente Cerebrovascular
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
IEEE Int Conf Rehabil Robot
Año:
2022
Tipo del documento:
Article
Pais de publicación:
Estados Unidos