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Fingers

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Decoding finger movement patterns from microscopic neural drive information based on deep learning.

Medical engineering & physics
Recent development of surface electromyogram (sEMG) decomposition technique provides a good basis of decoding movements from individual motor unit (MU) activities that directly representing microscopic neural drives. How to interpret the function and...

A 3D Printed Soft Robotic Hand With Embedded Soft Sensors for Direct Transition Between Hand Gestures and Improved Grasping Quality and Diversity.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In this study, a three-dimensional (3D) printed soft robotic hand with embedded soft sensors, intended for prosthetic applications is designed and developed to efficiently operate with new-generation myoelectric control systems, e.g., pattern recogni...

A generic neural network model to estimate populational neural activity for robust neural decoding.

Computers in biology and medicine
BACKGROUND: Robust and continuous neural decoding is crucial for reliable and intuitive neural-machine interactions. This study developed a novel generic neural network model that can continuously predict finger forces based on decoded populational m...

Designing a Contact Fingertip Sensor Made Using a Soft 3D Printing Technique.

Soft robotics
The development of highly compliant materials and actuators has enabled the design of soft robots that can be applied in rescue operations, in secure human-robot interactions, to manipulate fragile devices or objects, and for robot locomotion within ...

Stiffness-Tunable Soft Gripper with Soft-Rigid Hybrid Actuation for Versatile Manipulations.

Soft robotics
Highly flexible and environmentally adaptive soft robots have received considerable attention. There remains a demand for soft robots to realize the stiffness modulation and variable workspace for robust and versatile manipulations. This article pres...

Reliability Analysis for Finger Movement Recognition With Raw Electromyographic Signal by Evidential Convolutional Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Hand gesture recognition with surface electromyography (sEMG) is indispensable for Muscle-Gesture-Computer Interface. The usual focus of it is upon performance evaluation involving the accuracy and robustness of hand gesture recognition. However, add...

Functional cortical localization of tongue movements using corticokinematic coherence with a deep learning-assisted motion capture system.

Scientific reports
Corticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer is useful for the functional localization of the primary sensorimotor cortex (SM1). However, it is difficult to determine the tongue CKC beca...

Real time control and fabrication of a soft robotic glove by two parallel sensors with MBD approach.

Medical engineering & physics
Soft robotic gloves were designed to aid the rehabilitation process with hand pathologies and coordination of gripping exercises. The main issue in soft robotic actuators is to design a control strategy to overcome deformation in grasping exercises. ...

Adaptive Grasping of Moving Objects through Tactile Sensing.

Sensors (Basel, Switzerland)
A robot's ability to grasp moving objects depends on the availability of real-time sensor data in both the far-field and near-field of the gripper. This research investigates the potential contribution of tactile sensing to a task of grasping an obje...

Integrated linkage-driven dexterous anthropomorphic robotic hand.

Nature communications
Robotic hands perform several amazing functions similar to the human hands, thereby offering high flexibility in terms of the tasks performed. However, developing integrated hands without additional actuation parts while maintaining important functio...