2022/06/03 by Rhythm Arora, Matteo Lavit Nicora, Arora, Rhythm +11 · 1 citation
Computer Science · Engineering · Medicine · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Multi-Agent Systems and Negotiation #Robotics (cs.RO) #Robotics and Automated Systems #Stroke Rehabilitation and Recovery #cs.AI #cs.HC #cs.RO
paper · pdf · doi:10.48550/arxiv.2206.01587
The 5th Workshop on Behavior Adaptation Interaction and Learning for Assistive Robotics (BAILAR)
arxiv created 2022/06/03 · openalex publication_date 2022/06/03 · arxiv updated 2022/06/06 · openalex created_date 2023/02/16 · openalex updated_date 2026/07/28
In today's world, many patients with cognitive impairments and motor dysfunction seek the attention of experts to perform specific conventional therapies to improve their situation. However, due to a lack of neurorehabilitation professionals, patients suffer from severe effects that worsen their condition. In this paper, we present a technological approach for a novel robotic neurorehabilitation training system. It relies on a combination of a rehabilitation device, signal classification methods, supervised machine learning models for training adaptation, training exercises, and socially interactive agents as a user interface. Together with a professional, the system can be trained towards the patient's specific needs. Furthermore, after a training phase, patients are enabled to train independently at home without the assistance of a physical therapist with a socially interactive agent in the role of a coaching assistant.