Minimally invasive robotic surgery allows for many advantages over traditional surgical procedures, but the loss of force feedback combined with a potential for strong grasping forces can result in excessive tissue damage. Single modality haptic feed...
Biometric authentication is the process of recognizing a person by means of his\her psychological or behavioral traits. One of the most important issues faced by the biometric system developer is to protect the template obtained from the biometric of...
INTRODUCTION: Plain hand radiographs are the first-line and most commonly used imaging methods for diagnosis or differential diagnosis of rheumatoid arthritis (RA) and for monitoring disease activity. In this study, we used plain hand radiographs and...
OBJECTIVE: The objective of this study was to investigate the feasibility of applying myoelectric pattern recognition for controlling a robotic hand in individuals with spinal cord injury (SCI).
We used a robotic-based THz imaging system to investigate the sub-surface structure of an artificially mummified ancient Egyptian human left hand. The results obtained are compared to the results of a conventional CT and a micro-CT scan. Using such a...
In this study, we propose a strategy for delicately grasping fragile objects using a robotic gripper with highly deformable fluid fingertips. In an earlier study, we developed a soft fingertip, referred to as a fluid fingertip, which was fabricated f...
The rubber hand illusion describes a phenomenon in which participants experience a rubber hand as being part of their body by the synchronous application of visuotactile stimulation to the real and the artificial limb. In the recently introduced robo...
IEEE transactions on pattern analysis and machine intelligence
Jan 22, 2019
In this paper, a feature boosting network is proposed for estimating 3D hand pose and 3D body pose from a single RGB image. In this method, the features learned by the convolutional layers are boosted with a new long short-term dependence-aware (LSTD...
Non-invasive, electroencephalography (EEG)-based brain-computer interfaces (BCIs) on motor imagery movements translate the subject's motor intention into control signals through classifying the EEG patterns caused by different imagination tasks, e.g....
Grasp affordances in robotics represent different ways to grasp an object involving a variety of factors from vision to hand control. A model of grasp affordances that is able to scale across different objects, features and domains is needed to provi...