AIMC Topic: Fingers

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Deep learning of Parkinson's movement from video, without human-defined measures.

Journal of the neurological sciences
BACKGROUND: The core clinical sign of Parkinson's disease (PD) is bradykinesia, for which a standard test is finger tapping: the clinician observes a person repetitively tap finger and thumb together. That requires an expert eye, a scarce resource, a...

Towards Efficient Neural Decoder for Dexterous Finger Force Predictions.

IEEE transactions on bio-medical engineering
OBJECTIVE: Dexterous control of robot hands requires a robust neural-machine interface capable of accurately decoding multiple finger movements. Existing studies primarily focus on single-finger movement or rely heavily on multi-finger data for decod...

Effect of task-oriented training assisted by force feedback hand rehabilitation robot on finger grasping function in stroke patients with hemiplegia: a randomised controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Over 80% of patients with stroke experience finger grasping dysfunction, affecting independence in activities of daily living and quality of life. In routine training, task-oriented training is usually used for functional hand training, w...

Development of a Two-Finger Haptic Robotic Hand with Novel Stiffness Detection and Impedance Control.

Sensors (Basel, Switzerland)
Haptic hands and grippers, designed to enable skillful object manipulation, are pivotal for high-precision interaction with environments. These technologies are particularly vital in fields such as minimally invasive surgery, where they enhance surgi...

Towards humanlike grasp in robotic hands: mechanical implementation of force synergies.

Bioinspiration & biomimetics
In the field of robotic hands, finger force coordination is usually achieved by complex mechanical structures and control systems. This study presents the design of a novel transmission system inspired from the physiological concept of force synergie...

A Sensorized Soft Robotic Hand with Adhesive Fingertips for Multimode Grasping and Manipulation.

Soft robotics
Soft robotic grippers excel at achieving conformal and reliable contact with objects without the need for complex control algorithms. However, they still lack in grasp and manipulation abilities compared with human hands. In this study, we present a ...

Enhancing the Versatility and Performance of Soft Robotic Grippers, Hands, and Crawling Robots Through Three-Dimensional-Printed Multifunctional Buckling Joints.

Soft robotics
Soft robotic grippers and hands offer adaptability, lightweight construction, and enhanced safety in human-robot interactions. In this study, we introduce vacuum-actuated soft robotic finger joints to overcome their limitations in stiffness, response...

Teleoperation of an Anthropomorphic Robot Hand with a Metamorphic Palm and Tunable-Stiffness Soft Fingers.

Soft robotics
Teleoperation in soft robotics can endow soft robots with the ability to perform complex tasks through human-robot interaction. In this study, we propose a teleoperated anthropomorphic soft robot hand with variable degrees of freedom (DOFs) and a met...

From Skin Movement to Wearable Robotics: The Case of Robotic Gloves.

Soft robotics
Previous research on wearable robotics focused on developing actuation mechanisms while overlooking influences of skin movement. During finger flexion, skins on the opisthenar and finger back are stretched. Impeding such skin movement will obstruct n...

A Multimodal Multilevel Converged Attention Network for Hand Gesture Recognition With Hybrid sEMG and A-Mode Ultrasound Sensing.

IEEE transactions on cybernetics
Gesture recognition based on surface electromyography (sEMG) has been widely used in the field of human-machine interaction (HMI). However, sEMG has limitations, such as low signal-to-noise ratio and insensitivity to fine finger movements, so we cons...