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Swarm-wavelet based Extreme Learning Machine for Finger Movement Classification on Transradial Amputees
(2016-06-06)
The use of a small number of surface
electromyography (EMG) channels on the transradial amputee
in a myoelectric controller is a big challenge. This paper
proposes a pattern recognition system using an extreme
learning ...
A novel extreme learning machine for dimensionality reduction on finger movement classification using sEMG
(2016-06-06)
Projecting a high dimensional feature into a lowdimensional
feature without compromising the feature
characteristic is a challenging task. This paper proposes a novel
dimensionality reduction constituted from the ...
Swarm-based Extreme Learning Machine for Finger Movement Recognition
(2016-06-06)
An accurate finger movement recognition is
required in many robotics prosthetics and assistive hand
devices. The use of a small number of Electromyography
(EMG) channels for classifying the finger movement is a
challenging ...
Two-Channel Surface Electromyography for Individual and Combined Finger Movements
(2016-06-06)
This paper proposes the pattern recognition
system for individual and combined finger movements by using
two channel electromyography (EMG) signals. The proposed
system employs Spectral Regression Discriminant ...
Evaluation of Randomized Variable Translation Wavelet Neural Networks
(2018-04-04)
A variable translation wavelet neural network (VT-WNN) is a type
of wavelet neural network that is able to adapt to the changes in the input.
Different learning algorithms have been proposed such as backpropagation ...
Adaptive Wavelet Extreme Learning Machine (AW-ELM) for Index Finger Recognition Using Two-Channel Electromyography
(2018-04-04)
This paper proposes a new structure of wavelet extreme learning machine
i.e.
an
adaptive
wavelet
extreme
learning
machine
(AW-ELM)
for
finger
motion
recognition using only two EMG channels. The adaptation ...
Myoelectric control systems for hand rehabilitation device: a review
(2018-04-04)
One of the challenges of the hand rehabilitation
device is to create a smooth interaction between the device and
user. The smooth interaction can be achieved by considering
myoelectric signal generated by human's muscle. ...
AW-ELM-based Crouch Gait Recognition after ischemic stroke
(2018-04-04)
Crouch Gait (CG) can be observed in the
hemiplegia persons after ischemic stroke. Walking with Crouch
Gait (CG) shown a large gaits disorder. This paper explores the
use of adaptive wavelet extreme learning machine ...
A robust myoelectric pattern recognition using online sequential extreme learning machine for finger movement classification
(2017-08-29)
A robust myoelectric pattern-recognition-system requires a system that should work in the real application as good as in the laboratory. However, this demand should be handled properly and rigorously to achieve a robust ...
Continuous Prediction of Shoulder Joint Angle in Real-Time
(2017-10-11)
Continuous prediction of dynamic joint angle
from surface electromyography (sEMG) signal is one of the
most important applications in rehabilitation area for stroke
survivors as these can directly reflect the user motor ...