Toward higher-performance bionic limbs for wider clinical use
Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by
the user as belonging to their own body. Robotic limbs can convey information about the …
the user as belonging to their own body. Robotic limbs can convey information about the …
Flexible electronics and devices as human–machine interfaces for medical robotics
Medical robots are invaluable players in non‐pharmaceutical treatment of disabilities.
Particularly, using prosthetic and rehabilitation devices with human–machine interfaces can …
Particularly, using prosthetic and rehabilitation devices with human–machine interfaces can …
All-printed soft human-machine interface for robotic physicochemical sensing
Ultrasensitive multimodal physicochemical sensing for autonomous robotic decision-making
has numerous applications in agriculture, security, environmental protection, and public …
has numerous applications in agriculture, security, environmental protection, and public …
Improved control of a prosthetic limb by surgically creating electro-neuromuscular constructs with implanted electrodes
Remnant muscles in the residual limb after amputation are the most common source of
control signals for prosthetic hands, because myoelectric signals can be generated by the …
control signals for prosthetic hands, because myoelectric signals can be generated by the …
Deep learning for electromyographic hand gesture signal classification using transfer learning
U Côté-Allard, CL Fall, A Drouin… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
In recent years, deep learning algorithms have become increasingly more prominent for
their unparalleled ability to automatically learn discriminant features from large amounts of …
their unparalleled ability to automatically learn discriminant features from large amounts of …
Real-time EMG based pattern recognition control for hand prostheses: A review on existing methods, challenges and future implementation
Upper limb amputation is a condition that significantly restricts the amputees from performing
their daily activities. The myoelectric prosthesis, using signals from residual stump muscles …
their daily activities. The myoelectric prosthesis, using signals from residual stump muscles …
A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition
The surface electromyography (sEMG)-based gesture recognition with deep learning
approach plays an increasingly important role in human-computer interaction. Existing deep …
approach plays an increasingly important role in human-computer interaction. Existing deep …
Deep learning for EMG-based human-machine interaction: A review
D Xiong, D Zhang, X Zhao… - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
Electromyography (EMG) has already been broadly used in human-machine interaction
(HMI) applications. Determining how to decode the information inside EMG signals robustly …
(HMI) applications. Determining how to decode the information inside EMG signals robustly …
Gesture recognition using surface electromyography and deep learning for prostheses hand: state-of-the-art, challenges, and future
W Li, P Shi, H Yu - Frontiers in neuroscience, 2021 - frontiersin.org
Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life,
and limits their performance in activities of daily life. The realization of natural control for …
and limits their performance in activities of daily life. The realization of natural control for …
Comparison of six electromyography acquisition setups on hand movement classification tasks
Hand prostheses controlled by surface electromyography are promising due to the non-
invasive approach and the control capabilities offered by machine learning. Nevertheless …
invasive approach and the control capabilities offered by machine learning. Nevertheless …