TY - JOUR
T1 - Intelligent Robotics in Pediatric Cooperative Neurorehabilitation
T2 - A Review
AU - Ezra Tsur, Elishai
AU - Elkana, Odelia
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/3
Y1 - 2024/3
N2 - The landscape of neurorehabilitation is undergoing a profound transformation with the integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing need for advancements in pediatric neurorehabilitation and underscores the pivotal role of AI-driven robotics in addressing existing gaps. By leveraging AI technologies, robotic systems can transcend the limitations of preprogrammed guidelines and adapt to individual patient needs, thereby fostering patient-centric care. This review explores recent strides in social and diagnostic robotics, physical therapy, assistive robotics, smart interfaces, and cognitive training within the context of pediatric neurorehabilitation. Furthermore, it examines the impact of emerging AI techniques, including artificial emotional intelligence, interactive reinforcement learning, and natural language processing, on enhancing cooperative neurorehabilitation outcomes. Importantly, the review underscores the imperative of responsible AI deployment and emphasizes the significance of unbiased, explainable, and interpretable models in fostering adaptability and effectiveness in pediatric neurorehabilitation settings. In conclusion, this review provides a comprehensive overview of the evolving landscape of AI-driven robotics in pediatric neurorehabilitation and offers valuable insights for clinicians, researchers, and policymakers.
AB - The landscape of neurorehabilitation is undergoing a profound transformation with the integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing need for advancements in pediatric neurorehabilitation and underscores the pivotal role of AI-driven robotics in addressing existing gaps. By leveraging AI technologies, robotic systems can transcend the limitations of preprogrammed guidelines and adapt to individual patient needs, thereby fostering patient-centric care. This review explores recent strides in social and diagnostic robotics, physical therapy, assistive robotics, smart interfaces, and cognitive training within the context of pediatric neurorehabilitation. Furthermore, it examines the impact of emerging AI techniques, including artificial emotional intelligence, interactive reinforcement learning, and natural language processing, on enhancing cooperative neurorehabilitation outcomes. Importantly, the review underscores the imperative of responsible AI deployment and emphasizes the significance of unbiased, explainable, and interpretable models in fostering adaptability and effectiveness in pediatric neurorehabilitation settings. In conclusion, this review provides a comprehensive overview of the evolving landscape of AI-driven robotics in pediatric neurorehabilitation and offers valuable insights for clinicians, researchers, and policymakers.
KW - adaptive behavior
KW - artificial intelligence (AI)
KW - assistive robotics
KW - cognitive training
KW - intelligent robotics
KW - neurorehabilitation
KW - pediatric neurorehabilitation
KW - personalized rehabilitation
KW - responsible AI
KW - social robotics
UR - http://www.scopus.com/inward/record.url?scp=85188947978&partnerID=8YFLogxK
U2 - 10.3390/robotics13030049
DO - 10.3390/robotics13030049
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AN - SCOPUS:85188947978
SN - 2218-6581
VL - 13
JO - Robotics
JF - Robotics
IS - 3
M1 - 49
ER -