Employing Socially Interactive Agents for Robotic Neurorehabilitation Training

• URL: http://arxiv.org/abs/2206.01587v1
• Date: Fri, 3 Jun 2022 14:17:37 GMT
• Title: Employing Socially Interactive Agents for Robotic Neurorehabilitation Training
• Authors: Rhythm Arora, Matteo Lavit Nicora, Pooja Prajod, Daniele Panzeri, Elisabeth Andr\'e, Patrick Gebhard, Matteo Malosio
• Abstract summary: 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.
• Score: 0.2886273197127056
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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