Socially interactive agents for robotic neurorehabilitation training: conceptualization and proof-of-concept study.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Frontiers in Artificial Intelligence Pub Date : 2024-11-28 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1441955
Rhythm Arora, Pooja Prajod, Matteo Lavit Nicora, Daniele Panzeri, Giovanni Tauro, Rocco Vertechy, Matteo Malosio, Elisabeth André, Patrick Gebhard
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引用次数: 0

Abstract

Introduction: 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.

Methods: 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.

Results and discussion: 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.

用于机器人神经康复训练的社交互动代理:概念化和概念验证研究。
具有不同运动能力的个体通常受益于强化和专门的康复治疗,旨在增强他们的功能恢复。然而,挑战在于神经康复专业人员的可用性有限,阻碍了有效提供必要水平的护理。机器人设备在减少治疗过程中对医务人员的依赖方面具有巨大的潜力,但与此同时,它们通常缺乏传统面对面治疗所提供的关键的人际互动和动力。方法:为了弥补这一差距,我们引入了一种基于人工智能的系统,旨在在神经康复训练期间提供个性化的院外援助。该系统包括康复训练装置、情感信号分类模型、训练练习和社会交互代理作为用户界面。在专业人员的协助下,设想的系统被设计为适应个体患者独特的康复需求。从概念上讲,在初步设置和指导阶段之后,患者就可以在舒适的家中自主地继续他们的康复方案,由一个充当虚拟教练助理的社会互动代理来促进。我们的方法包括将交互式社会意识虚拟代理集成到神经康复机器人框架中,其主要目标是重现面对面康复过程中固有的社会方面。我们还进行了可行性研究,在健康患者中测试该框架。结果和讨论:我们的初步调查结果表明,参与者表现出适应系统的倾向。值得注意的是,在拟议的演习中,交互代理的存在并没有成为分散注意力的来源;相反,它对用户粘性产生了积极影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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