Research on affective communication for socially assistive robots has been conducted to enable physical robots to perceive, express, and respond emotionally. However, the use of affective computing in social robots has been limited, especially when social robots are designed for children, and especially those with autism spectrum disorder (ASD). Social robots are based on cognitive-affective models, which allow them to communicate with people following social behaviors and rules. However, interactions between a child and a robot may change or be different compared to those with an adult or when the child has an emotional deficit. In this study, we systematically reviewed studies related to computational models of emotions for children with ASD. We used the Scopus, WoS, Springer, and IEEE-Xplore databases to answer different research questions related to the definition, interaction, and design of computational models supported by theoretical psychology approaches from 1997 to 2021. Our review found 46 articles; not all the studies considered children or those with ASD.
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http://dx.doi.org/10.3390/s21155166 | DOI Listing |
J Neurosurg Spine
January 2025
1Department of Spine Surgery, Hospital for Special Surgery, New York.
Objective: When creating minimally invasive spine fusion constructs, accurate pedicle screw fixation is essential for biomechanical strength and avoiding complications arising from delicate surrounding structures. As research continues to analyze how to improve accuracy, long-term patient outcomes based on screw accuracy remain understudied. The objective of this study was to analyze long-term patient outcomes based on screw accuracy.
View Article and Find Full Text PDFPLoS One
January 2025
Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania, Brazil.
This paper proposes the use of artificial intelligence techniques, specifically the nnU-Net convolutional neural network, to improve the identification of left ventricular walls in images of myocardial perfusion scintigraphy, with the objective of improving the diagnosis and treatment of coronary artery disease. The methodology included data collection in a clinical environment, followed by data preparation and analysis using the 3D Slicer Platform for manual segmentation, and subsequently, the application of artificial intelligence models for automated segmentation, focusing on the efficiency of identifying the walls of the left ventricular. A total of 83 clinical routine exams were collected, each exam containing 50 slices, which is 4,150 images.
View Article and Find Full Text PDFEvol Comput
January 2025
Sorbonne Université, CNRS, ISIR., Paris, 75005, France
Quality-Diversity (QD) methods are algorithms that aim to generate a set of diverse and highperforming solutions to a given problem. Originally developed for evolutionary robotics, most QD studies are conducted on a limited set of domains'mainly applied to locomotion, where the fitness and the behavior signal are dense. Grasping is a crucial task for manipulation in robotics.
View Article and Find Full Text PDFSci Adv
January 2025
School of Chemical Engineering, Pusan National University, Busan, Republic of Korea.
The development of fibrous actuators with diverse actuation modes is expected to accelerate progress in active textiles, robotics, wearable electronics, and haptics. Despite the advances in responsive polymer-based actuating fibers, the available actuation modes are limited by the exclusive reliance of current technologies on thermotropic contraction along the fiber axis. To address this gap, the present study describes a reversible and spontaneous thermotropic elongation (~30%) in liquid crystal elastomer fibers produced via ultraviolet-assisted melt spinning.
View Article and Find Full Text PDFSci Adv
January 2025
School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
Electronic skins endow robots with sensory functions but often lack the multifunctionality of natural skin, such as switchable adhesion. Current smart adhesives based on elastomers have limited adhesion tunability, which hinders their effective use for both carrying heavy loads and performing dexterous manipulations. Here, we report a versatile, one-size-fits-all robotic adhesive skin using shape memory polymers with tunable rubber-to-glass phase transitions.
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