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Deep learning approaches for enhanced lower-limb exoskeleton control: A review
Recent advancements in robotics have pushed the development of active exoskeletons and
orthoses for assistive, augmentative, and rehabilitative purposes. Deep Learning …
orthoses for assistive, augmentative, and rehabilitative purposes. Deep Learning …
Deep learning for quantified gait analysis: a systematic literature review
Over the past few years, there has been notable advancement in the field of Quantified Gait
Analysis (QGA), thanks to machine learning techniques. QGA and gait prediction are areas …
Analysis (QGA), thanks to machine learning techniques. QGA and gait prediction are areas …
Gait reference trajectory generation at different walking speeds using LSTM and CNN
Rehabilitation robots are gaining significant popularity for impaired gait rehabilitation.
However, to make the recovering individual feel natural while walking and restore their …
However, to make the recovering individual feel natural while walking and restore their …
Lower-limb joint torque prediction using LSTM neural networks and transfer learning
Estimation of joint torque during movement provides important information in several
settings, such as effect of athletes' training or of a medical intervention, or analysis of the …
settings, such as effect of athletes' training or of a medical intervention, or analysis of the …
[HTML][HTML] Federated compressed learning edge computing framework with ensuring data privacy for PM2. 5 prediction in smart city sensing applications
The sparse data in PM2. 5 air quality monitoring systems is frequently happened on large-
scale smart city sensing applications, which is collected via massive sensors. Moreover, it …
scale smart city sensing applications, which is collected via massive sensors. Moreover, it …
Deep learning models for stable gait prediction applied to exoskeleton reference trajectories for children with cerebral palsy
Gait trajectory prediction models have several applications in exoskeleton control; they can
be used as feed-forward input to low-level controllers and to generate reference/target …
be used as feed-forward input to low-level controllers and to generate reference/target …
Prediction of gait trajectories based on the Long Short Term Memory neural networks
The forecasting of lower limb trajectories can improve the operation of assistive devices and
minimise the risk of trip** and balance loss. The aim of this work was to examine four …
minimise the risk of trip** and balance loss. The aim of this work was to examine four …
[HTML][HTML] Motion trajectories prediction of lower limb exoskeleton based on long short-term memory (LSTM) networks
A typical man–machine coupling system could provide the wearer a coordinated and
assisted movement by the lower limb exoskeleton. The process of cooperative movement …
assisted movement by the lower limb exoskeleton. The process of cooperative movement …
[HTML][HTML] Gait trajectory prediction on an embedded microcontroller using deep learning
Achieving a normal gait trajectory for an amputee's active prosthesis is challenging due to its
kinematic complexity. Accordingly, lower limb gait trajectory kinematics and gait phase …
kinematic complexity. Accordingly, lower limb gait trajectory kinematics and gait phase …
Reservoir computing model for human hand locomotion signal classification
Human-movement recognition is a novel challenge in soft robotics. In recent years, there
have been several attempts to develop soft wearable devices for supporting human-robot …
have been several attempts to develop soft wearable devices for supporting human-robot …