AIMC Topic: Artificial Limbs

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Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand.

Journal of neuroengineering and rehabilitation
BACKGROUND: State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently...

Transduction Mechanisms, Micro-Structuring Techniques, and Applications of Electronic Skin Pressure Sensors: A Review of Recent Advances.

Sensors (Basel, Switzerland)
Electronic skin (e-skin), which is an electronic surrogate of human skin, aims to recreate the multifunctionality of skin by using sensing units to detect multiple stimuli, while keeping key features of skin such as low thickness, stretchability, fle...

3D Printed Robot Hand Structure Using Four-Bar Linkage Mechanism for Prosthetic Application.

Sensors (Basel, Switzerland)
Trans-radial prosthesis is a wearable device that intends to help amputees under the elbow to replace the function of the missing anatomical segment that resembles an actual human hand. However, there are some challenging aspects faced mainly on the ...

Computer Vision-Based Grasp Pattern Recognition With Application to Myoelectric Control of Dexterous Hand Prosthesis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To achieve suitable grasps over various objects, a novel computer vision-based classification method assorting objects into different grasp patterns is propose...

Intra-cortical brain-machine interfaces for controlling upper-limb powered muscle and robotic systems in spinal cord injury.

Clinical neurology and neurosurgery
OBJECTIVE: Intracortical brain-machine interface (iBMI) is an assistive strategy to restore lost sensorimotor function by bridging the disrupted neural pathways to reanimate paralyzed limbs. However, to date, none of the studies explored the trade-of...

A practical 3D-printed soft robotic prosthetic hand with multi-articulating capabilities.

PloS one
Soft robotic hands with monolithic structure have shown great potential to be used as prostheses due to their advantages to yield light weight and compact designs as well as its ease of manufacture. However, existing soft prosthetic hands design were...

Performance Evaluation of Convolutional Neural Network for Hand Gesture Recognition Using EMG.

Sensors (Basel, Switzerland)
Electromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still ins...

A Deep Transfer Learning Approach to Reducing the Effect of Electrode Shift in EMG Pattern Recognition-Based Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
An important barrier to commercialization of pattern recognition myoelectric control of prostheses is the lack of robustness to confounding factors such as electrode shift, skin impedance variations, and learning effects. To overcome this challenge, ...

The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses.

IEEE transactions on haptics
While prosthetic fitting after upper-limb loss allows for restoration of motor functions, it deprives the amputee of tactile sensations that are essential for grasp control in able-bodied subjects. Therefore, it is commonly assumed that restoring the...

A Fully Embedded Adaptive Real-Time Hand Gesture Classifier Leveraging HD-sEMG and Deep Learning.

IEEE transactions on biomedical circuits and systems
This paper presents a real-time fine gesture recognition system for multi-articulating hand prosthesis control, using an embedded convolutional neural network (CNN) to classify hand-muscle contractions sensed at the forearm. The sensor consists in a ...