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 …
Wearable and flexible textile electrodes for biopotential signal monitoring: A review
Wearable electronics is a rapidly growing field that recently started to introduce successful
commercial products into the consumer electronics market. Employment of biopotential …
commercial products into the consumer electronics market. Employment of biopotential …
Deep learning with convolutional neural networks applied to electromyography data: A resource for the classification of movements for prosthetic hands
Natural control methods based on surface electromyography (sEMG) and pattern
recognition are promising for hand prosthetics. However, the control robustness offered by …
recognition are promising for hand prosthetics. However, the control robustness offered by …
Materials and optimized designs for human-machine interfaces via epidermal electronics
Thin, soft, and elastic electronics with physical properties well matched to the epidermis can
be conformally and robustly integrated with the skin. Materials and optimized designs for …
be conformally and robustly integrated with the skin. Materials and optimized designs 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 …
Self-recalibrating surface EMG pattern recognition for neuroprosthesis control based on convolutional neural network
Hand movement classification based on surface electromyography (sEMG) pattern
recognition is a promising approach for upper limb neuroprosthetic control. However …
recognition is a promising approach for upper limb neuroprosthetic control. However …
Surface EMG-based inter-session gesture recognition enhanced by deep domain adaptation
High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity
from a restricted area of the skin by using two dimensional arrays of closely spaced …
from a restricted area of the skin by using two dimensional arrays of closely spaced …
Simultaneous control of multiple functions of bionic hand prostheses: Performance and robustness in end users
Myoelectric hand prostheses are usually controlled with two bipolar electrodes located on
the flexor and extensor muscles of the residual limb. With clinically established techniques …
the flexor and extensor muscles of the residual limb. With clinically established techniques …
Regression convolutional neural network for improved simultaneous EMG control
Objective. Deep learning models can learn representations of data that extract useful
information in order to perform prediction without feature engineering. In this paper, an …
information in order to perform prediction without feature engineering. In this paper, an …
A deep transfer learning approach to reducing the effect of electrode shift in EMG pattern recognition-based control
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 …
prostheses is the lack of robustness to confounding factors such as electrode shift, skin …