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Bio-Inspired Haptic Feedback for Artificial Palpation in Robotic Surgery.

IEEE transactions on bio-medical engineering
Adding haptic feedback has been reported to improve the outcome of minimally invasive robotic surgery. In this study, we seek to determine whether an algorithm based on simulating responses of a cutaneous afferent population can be implemented to imp...

Robust Control of a New Asymmetric Teleoperation Robot Based on a State Observer.

Sensors (Basel, Switzerland)
This study is mainly about the designation of a new type of haptic device and an asymmetric teleoperation robot system. Aiming at the problems of tracking and transparency of an asymmetric teleoperation system, a robust control algorithm based on a s...

Enhancing the Localization of Uterine Leiomyomas Through Cutaneous Softness Rendering for Robot-Assisted Surgical Palpation Applications.

IEEE transactions on haptics
Integrating tactile feedback for lump localization in Robot-assisted Minimally Invasive Surgery (RMIS) represents an open research issue, which is still far to be solved. Main reasons for this are related e.g. to the need for a transparent connection...

Bipartite synchronization of signed networks via aperiodically intermittent control based on discrete-time state observations.

Neural networks : the official journal of the International Neural Network Society
In this paper, bipartite synchronization of signed networks with stochastic disturbances via aperiodically intermittent control is investigated. The aperiodically intermittent control presented is based on discrete-time state observations rather than...

Improved protein relative solvent accessibility prediction using deep multi-view feature learning framework.

Analytical biochemistry
The accurate prediction of the relative solvent accessibility of a protein is critical to understanding its 3D structure and biological function. In this study, a novel deep multi-view feature learning (DMVFL) framework that integrates three differen...

Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery.

IEEE transactions on neural networks and learning systems
Symbolic regression is a powerful technique to discover analytic equations that describe data, which can lead to explainable models and the ability to predict unseen data. In contrast, neural networks have achieved amazing levels of accuracy on image...

The Flow of Axonal Information Among Hippocampal Subregions: 1. Feed-Forward and Feedback Network Spatial Dynamics Underpinning Emergent Information Processing.

Frontiers in neural circuits
The tri-synaptic pathway in the mammalian hippocampus enables cognitive learning and memory. Despite decades of reports on anatomy and physiology, the functional architecture of the hippocampal network remains poorly understood in terms of the dynami...

Intuitive Spatial Tactile Feedback for Better Awareness about Robot Trajectory during Human-Robot Collaboration.

Sensors (Basel, Switzerland)
In this work, we extend the previously proposed approach of improving mutual perception during human-robot collaboration by communicating the robot's motion intentions and status to a human worker using hand-worn haptic feedback devices. The improvem...

Observer-based event-triggered control for zero-sum games of input constrained multi-player nonlinear systems.

Neural networks : the official journal of the International Neural Network Society
In this paper, an event-triggered control (ETC) method is investigated to solve zero-sum game (ZSG) problems of unknown multi-player continuous-time nonlinear systems with input constraints by using adaptive dynamic programming (ADP). To relax the re...

The Adaptive Dynamic Programming Toolbox.

Sensors (Basel, Switzerland)
The paper develops the adaptive dynamic programming toolbox (ADPT), which is a MATLAB-based software package and computationally solves optimal control problems for continuous-time control-affine systems. The ADPT produces approximate optimal feedbac...