Socially interactive agents for robotic neurorehabilitation training: conceptualization and proof-of-concept study DOI Creative Commons

Rhythm Arora,

Pooja Prajod, Matteo Lavit Nicora

et al.

Frontiers in Artificial Intelligence, Journal Year: 2024, Volume and Issue: 7

Published: Nov. 28, 2024

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 restricted availability of neurorehabilitation professionals, hindering effective delivery necessary level care. Robotic devices hold great potential reducing dependence on medical personnel during therapy but, same time, they generally lack crucial human interaction motivation that traditional in-person sessions provide. Methods To bridge this gap, we introduce an AI-based system delivering personalized, out-of-hospital assistance training. This includes a training device, affective signal classification models, exercises, socially interactive agent as user interface. With professional, envisioned is designed to be tailored accommodate unique requirements individual patient. Conceptually, after preliminary setup instruction phase, patient equipped continue regimen autonomously comfort home, facilitated by functioning virtual coaching assistant. Our approach involves integration socially-aware into robotic framework, primary objective recreating social aspects inherent sessions. We also conducted feasibility study test framework healthy patients. Results discussion The results our investigation indicate participants demonstrated propensity adapt system. Notably, presence proposed exercises did not act source distraction; instead, it positively impacted users' engagement.

Language: Английский

Socially interactive agents for robotic neurorehabilitation training: conceptualization and proof-of-concept study DOI Creative Commons

Rhythm Arora,

Pooja Prajod, Matteo Lavit Nicora

et al.

Frontiers in Artificial Intelligence, Journal Year: 2024, Volume and Issue: 7

Published: Nov. 28, 2024

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 restricted availability of neurorehabilitation professionals, hindering effective delivery necessary level care. Robotic devices hold great potential reducing dependence on medical personnel during therapy but, same time, they generally lack crucial human interaction motivation that traditional in-person sessions provide. Methods To bridge this gap, we introduce an AI-based system delivering personalized, out-of-hospital assistance training. This includes a training device, affective signal classification models, exercises, socially interactive agent as user interface. With professional, envisioned is designed to be tailored accommodate unique requirements individual patient. Conceptually, after preliminary setup instruction phase, patient equipped continue regimen autonomously comfort home, facilitated by functioning virtual coaching assistant. Our approach involves integration socially-aware into robotic framework, primary objective recreating social aspects inherent sessions. We also conducted feasibility study test framework healthy patients. Results discussion The results our investigation indicate participants demonstrated propensity adapt system. Notably, presence proposed exercises did not act source distraction; instead, it positively impacted users' engagement.

Language: Английский

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