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Hand

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Source Aware Deep Learning Framework for Hand Kinematic Reconstruction Using EEG Signal.

IEEE transactions on cybernetics
The ability to reconstruct the kinematic parameters of hand movement using noninvasive electroencephalography (EEG) is essential for strength and endurance augmentation using exoskeleton/exosuit. For system development, the conventional classificatio...

Mixed -synthesis tracking control and disturbance rejection in a robotic digit of an impaired human hand for anthropomorphic coordination.

Biological cybernetics
In a partially impaired anthropomorphic hand, maintaining the movement coordination of the robotic digits with the central nervous system (CNS) and natural digits is crucial for robust performance. A challenge in the control perspective of movement c...

Impairments of the arm and hand are highly correlated during subacute stroke.

Journal of rehabilitation medicine
BACKGROUND: The classical description of poststroke upper limb impairment follows a proximalto-distal impairment gradient. Previous studies are equivocal on whether the hand is more impaired than the arm.

Using artificial intelligence models to evaluate envisaged points initially: A pilot study.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The morphology of the finger bones in hand-wrist radiographs (HWRs) can be considered as a radiological skeletal maturity indicator, along with the other indicators. This study aims to validate the anatomical landmarks envisaged to be used for classi...

Soft Robotics Enables Neuroprosthetic Hand Design.

ACS nano
Development and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although p...

A Deep Q-Network based hand gesture recognition system for control of robotic platforms.

Scientific reports
Hand gesture recognition (HGR) based on electromyography signals (EMGs) and inertial measurement unit signals (IMUs) has been investigated for human-machine applications in the last few years. The information obtained from the HGR systems has the pot...

A hierarchical sensorimotor control framework for human-in-the-loop robotic hands.

Science robotics
Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nerv...

Exploring Tactile Temporal Features for Object Pose Estimation during Robotic Manipulation.

Sensors (Basel, Switzerland)
Dexterous robotic manipulation tasks depend on estimating the state of in-hand objects, particularly their orientation. Although cameras have been traditionally used to estimate the object's pose, tactile sensors have recently been studied due to the...

Hand Gesture Interface for Robot Path Definition in Collaborative Applications: Implementation and Comparative Study.

Sensors (Basel, Switzerland)
The article explores the possibilities of using hand gestures as a control interface for robotic systems in a collaborative workspace. The development of hand gesture control interfaces has become increasingly important in everyday life as well as pr...

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping.

Journal of visualized experiments : JoVE
To grasp an object successfully, we must select appropriate contact regions for our hands on the surface of the object. However, identifying such regions is challenging. This paper describes a workflow to estimate the contact regions from marker-base...