|
back propagation network |
2 |
|
control |
2 |
|
deep belief networks |
2 |
|
deep learning |
2 |
|
electromyography |
2 |
|
hot line work robot |
2 |
|
joint angle estimation |
2 |
|
motors and reducers |
2 |
|
multichannel surface emg |
2 |
|
principal components analysis |
2 |
|
restricted boltzmann machines |
2 |
|
static analysis |
2 |
|
structure design |
2 |
|
teleoperation framework |
2 |
|
teleoperation testbed |
2 |
|
three axis mechanical arm |
2 |
|
three-dimensional model |
2 |
|
3d |
1 |
|
action recognition |
1 |
|
adaptive backstep-ping control |
1 |
|
adaptive control |
1 |
|
adaptive neuro fuzzy inference system(anfis) |
1 |
|
assist-as-needed |
1 |
|
asynchronous system |
1 |
|
attention mechanism |
1 |
|
biomechanical model |
1 |
|
biomechnical |
1 |
|
brain-computer interface |
1 |
|
brain-computer interface (bci) |
1 |
|
brain-controlled prostheses |
1 |
|
brain-machine interfaces |
1 |
|
bws system |
1 |
|
contact force |
1 |
|
continuous motion recognition |
1 |
|
control method using emg signals |
1 |
|
control strategy |
1 |
|
convolutional neural network |
1 |
|
convolutional neural network (cnn) |
1 |
|
data fusion |
1 |
|
decoding of emg signals |
1 |
|
deep auto-encoder |
1 |
|
domain adaptation (da) |
1 |
|
driving force |
1 |
|
dynamic balance |
1 |
|
eeg generation |
1 |
|
electroencephalogram |
1 |
|
environment uncertainties |
1 |
|
exoskeleton |
1 |
|
finger gesture recognition |
1 |
|
fokker-planck equation |
1 |
|
forward biomechanics |
1 |
|
four-stte midel |
1 |
|
gait |
1 |
|
gait analysis |
1 |
|
gait event |
1 |
|
gait parameter |
1 |
|
gait phase recognition |
1 |
|
gait trajectory tracking control |
1 |
|
high-density surface emg (hd-semg) |
1 |
|
human-machine interaction |
1 |
|
humanoid robots |
1 |
|
hurst exponent |
1 |
|
hydraulic system |
1 |
|
induction motor |
1 |
|
information fusion |
1 |
|
insole pressure |
1 |
|
joint torque |
1 |
|
joint torque prediction |
1 |
|
labview |
1 |
|
link mechanism |
1 |
|
lower limb |
1 |
|
lower limb exoskeleton robot |
1 |
|
lower limb rehabilitation robot |
1 |
|
lower limbs rehabilitation robot |
1 |
|
measurement system |
1 |
|
medical robot |
1 |
|
microscopis |
1 |
|
model calibration |
1 |
|
modeling |
1 |
|
molecular motor |
1 |
|
motion planning |
1 |
|
multichannel |
1 |
|
muscle contraction |
1 |
|
muscle fibes |
1 |
|
muscle model |
1 |
|
musculoskeletal model |
1 |
|
neurologic injury |
1 |
|
non-equilibrium statistical mechanics |
1 |
|
parameter estimation |
1 |
|
pd computed torque control |
1 |
|
perceptive control |
1 |
|
power matching |
1 |
|
power source characteristic |
1 |
|
pt100 |
1 |
|
rbf neural network compensation |
1 |
|
rehabilitation |
1 |
|
rehabilitation evaluation |
1 |
|
rehabilitation robot |
1 |
|
residual |
1 |
|
residual voltage |
1 |
|
resolver |
1 |
|
road engineering |
1 |
|
rotor broken bar |
1 |
|
scene graph steady-state visual evoked potentials (sg-ssvep) |
1 |
|
simulation |
1 |
|
skeletal muscle |
1 |
|
sliding mode |
1 |
|
state recognition |
1 |
|
step length |
1 |
|
subgrade |
1 |
|
support vector machine |
1 |
|
surface electromyography |
1 |
|
surface electromyography (semg) |
1 |
|
surface electromyography(emg) |
1 |
|
surface emg |
1 |
|
system integration |
1 |
|
time serials |
1 |
|
trajectory tracking |
1 |
|
treadmill |
1 |
|
volitional control |
1 |
|
wasserstein generative adversarial networks |
1 |
