Force and touch feedback, or haptics, can play a significant role in the realism of virtual reality surgical simulation. While it is accepted that simulators providing haptic feedback often outperform those that do not, little is known about the degree of haptic fidelity required to achieve simulation objectives. This article evaluates the effect that employing haptic rendering with different degrees of freedom (DOF) has on task performance in a virtual environment. Results show that 6-DOF haptic rendering significantly improves task performance over 3-DOF haptic rendering, even if computed torques are not displayed to the user. No significant difference could be observed between under-actuated (force only) and fully-actuated 6-DOF feedback in two surgically-motivated tasks.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Effects of Dual-Site Anodal Transcranial Direct Current Stimulation on Attention, Decision-Making, and Working Memory during Sports Fatigue in Elite Soccer Athletes.
J Integr Neurosci
January 2025
Sports, Exercise and Brain Sciences Laboratory, Sports Coaching College, Beijing Sport University, 100084 Beijing, China.
Background: Sports fatigue in soccer athletes has been shown to decrease neural activity, impairing cognitive function and negatively affecting motor performance. Transcranial direct current stimulation (tDCS) can alter cortical excitability, augment synaptic plasticity, and enhance cognitive function. However, its potential to ameliorate cognitive impairment during sports fatigue remains largely unexplored.
View Article and Find Full Text PDFMechanism evaluation of a digitally enabled rehabilitation intervention for people in aged care and neurological rehabilitation: mediation analysis of the AMOUNT trial.
Disabil Rehabil
January 2025
Sydney School of Health Sciences, Faculty of Medicine & Health, The University of Sydney, Sydney, Australia.
Purpose: To investigate potential mechanisms of a digital rehabilitation intervention associated with improved mobility among adults undertaking rehabilitation.
Materials And Methods: Causal mediation analysis of the AMOUNT trial (ACTRN12614000936628). Participants were randomised to digitally-enabled rehabilitation (virtual reality video games, activity monitors, and handheld computer devices prescribed by a physiotherapist) and usual care or usual care alone.
Patient Performance of Care Tasks During Acute Hospitalisation: A Scoping Review.
J Clin Nurs
January 2025
The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel.
Background: Patient self-care is established as improving outcomes, yet acute care in hospitals is provided such that patients tend to be passive recipients of care. Little is known about the extent and type of patient participation in treatment care tasks in acute hospital settings.
Aims: To map and synthesise available literature on self-performance of care tasks in acute hospital settings.
An Explainable CNN and Vision Transformer-Based Approach for Real-Time Food Recognition.
Nutrients
January 2025
Department of Computer Engineering, Inje University, Gimhae 50834, Republic of Korea.
Background: Food image recognition, a crucial step in computational gastronomy, has diverse applications across nutritional platforms. Convolutional neural networks (CNNs) are widely used for this task due to their ability to capture hierarchical features. However, they struggle with long-range dependencies and global feature extraction, which are vital in distinguishing visually similar foods or images where the context of the whole dish is crucial, thus necessitating transformer architecture.
View Article and Find Full Text PDFUnleashing the Potential of Pre-Trained Diffusion Models for Generalizable Person Re-Identification.
Sensors (Basel)
January 2025
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China.
Domain-generalizable re-identification (DG Re-ID) aims to train a model on one or more source domains and evaluate its performance on unseen target domains, a task that has attracted growing attention due to its practical relevance. While numerous methods have been proposed, most rely on discriminative or contrastive learning frameworks to learn generalizable feature representations. However, these approaches often fail to mitigate shortcut learning, leading to suboptimal performance.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!