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ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. Medicine and Public Health
Volume 7 - 2024 |
doi: 10.3389/frai.2024.1441955
This article is part of the Research Topic Advancements in AI-driven Multimodal Interfaces for Robot-Aided Rehabilitation View all articles
Socially Interactive Agents for Robotic Neurorehabilitation Training: Conceptualization and Proof-of-concept Study
Provisionally accepted- 1 German Research Center for Artificial Intelligence DFKI, Saarbrucken, Germany
- 2 Human-Centered Artificial Intelligence, Augsburg University, Augsburg, Germany, Augsburg, Baden-Württemberg, Germany
- 3 National Research Council of Italy, Lecco, Italy
- 4 Industrial Engineering Department, University of Bologna, Bologna, Emilia-Romagna, Italy
- 5 Scientific Institute IRCCS E. Medea, Bosisio Parini, Lecco, Italy
- 6 Human-Centered Artificial Intelligence, Augsburg University, Augsburg, Baden-Württemberg, Germany
Individuals with diverse motor abilities often benefit from intensive and specialized rehabilitation therapies aimed at enhancing their functional recovery. Nevertheless, the challenge lies in the restricted availability of neurorehabilitation professionals, hindering the effective delivery of the necessary level of care. Robotic devices hold great potential in reducing the dependence on medical personnel during therapy but, at the same time, they generally lack the crucial human interaction and motivation that traditional in-person sessions provide. To bridge this gap, we introduce an AI-based system aimed at delivering personalized, out-of-hospital assistance during neurorehabilitation training. This system includes a rehabilitation training device, affective signal classification models, training exercises, and a socially interactive agent as the user interface. With the assistance of a professional, the envisioned system is designed to be tailored to accommodate the unique rehabilitation requirements of an individual patient. Conceptually, after a preliminary setup and instruction phase, the patient is equipped to continue their rehabilitation regimen autonomously in the comfort of their home, facilitated by a socially interactive agent functioning as a virtual coaching assistant. Our approach involves the integration of an interactive socially-aware virtual agent into a neurorehabilitation robotic framework, with the primary objective of recreating the social aspects inherent to in-person rehabilitation sessions. We also conducted a feasibility study to test the framework with healthy patients. The results of our preliminary investigation indicate that participants demonstrated a propensity to adapt to the system. Notably, the presence of the interactive agent during the proposed exercises did not act as a source of distraction; instead, it positively impacted users' engagement.
Keywords: Social agent, virtual coach, Robotic neurorehabilitation, behaviour adaption, human-robot interaction, Affective Computing
Received: 31 May 2024; Accepted: 04 Nov 2024.
Copyright: © 2024 Arora, Prajod, Nicora, Panzeri, Tauro, Vertechy, Malosio, André and Gebhard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Rhythm Arora, German Research Center for Artificial Intelligence DFKI, Saarbrucken, Germany
Pooja Prajod, Human-Centered Artificial Intelligence, Augsburg University, Augsburg, Germany, Augsburg, Baden-Württemberg, Germany
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