Oct 13, 2023 · Experimental measurements have revealed that there exists an optimal size for input length in predicting hip joint moment with hip joint angle.

This study designs specific parameters to train a deep neural network for predicting hip joint moments and discusses the effects of the number of convolutional ...

This study designs specific parameters to train a deep neural network for predicting hip joint moments and discusses the effects of the number of convolutional ...

This study designs specific parameters to train a deep neural network for predicting hip joint moments and discusses the effects of the number of convolutional ...

Feb 26, 2021 · We developed and validated a gait phase estimator for real-time control of a robotic hip exoskeleton during multimodal locomotion.

This paper proposes a deep learning strategy using electromyography (EMG) signals to predict the human hip joint position and to determine the exoskeleton ...

The prediction of the hip moment is less sensitive to the anticipation time compared to the prediction of the knee and ankle moments, The moment prediction is ...

Jul 20, 2023 · In this paper, we propose a transformer-based model, TFSformer, to predict bilateral hip joint and knee joint angles through the plantar ...

Estimating the user's biological joint moment using ... • Neural networks can predict biological joint ... Hip Exoskeleton Control Using Neural Network-Based Hip ...

Oct 4, 2023 · Studies predicted lower-limb kinematics and kinetics using electroencephalograms (EEGs), electromyograms (EMGs), or a combination with kinematic ...