Objectives: To assess the efficacy of virtual reality (VR) in cardiopulmonary resuscitation (CPR) training.
Material And Methods: Experimental, analytic, cross-sectional study of a CPR training method using VR. Participants were randomly assigned to train in a control group or a VR group.
Results: The mean (SD) scores on a scale of 10 after training were 9.28 (0.91) in the VR group and 7.78 (1.63) in the control group, for a mean difference of 1.49 (95% CI, 0.96-2.02; P<.001). The VR group achieved a mean of 97.5 (9.7) compressions/min, versus 80.9 (7.7) compressions/min in the control group, for a mean difference of 16.6 compressions/min (95% CI, 15.0-18.2; P=.003). The mean compression depth in the VR group was 34.0 (6.5) mm, versus 27.9 (4.9) mm in the control group, for a mean difference of 6.7 (95% CI, 5.7-7.8; P<.001).
Conclusion: Training with VR can improve CPR theoretical knowledge and practical skills.
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IEEE Robot Autom Lett
November 2024
Department of Mechanical Engineering, Columbia University, New York, NY, 10027, USA.; Department of Rehabilitation and Regenerative Medicine, Columbia University, New York, NY, 10027, USA.
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December 2024
Neuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
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View Article and Find Full Text PDFFront Robot AI
December 2024
Department of Cognitive Robotics, Delft University of Technology, Delft, Netherlands.
In recent years, providing additional visual feedback about the interaction forces has been found to offer benefits to haptic-assisted teleoperation. However, there is limited insight into the effects of the design of force feedback-related visual cues and the type of visual display on the performance of teleoperation of robotic arms executing industrial tasks. In this study, we provide new insights into this interaction by extending these findings to the haptic assistance teleoperation of a simulated robotic arm in a virtual environment, in which the haptic assistance is comprised of a set of virtual fixtures.
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View Article and Find Full Text PDFCureus
December 2024
Psychology, University of Bath, Bath, GBR.
Artificial intelligence (AI) and mixed reality (MR), within human-computer interaction (HCI), are rapidly redefining areas of healthcare by introducing new approaches to patient care and clinical education. This editorial explores how these technologies, through Extended Mind Theory, enhance mental health treatment and medical training. AI-powered virtual therapists, using natural language processing and predictive analytics, provide accessible, personalized mental health support, allowing for remote and immersive therapy.
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