Using Convolutional Neural Network to Design and Predict the Forces and Kinematic Performance and External Rotation Moment of the Hip Joint in the Pelvis

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Abstract

In order to improve the dynamic and kinematic adaptability of the hip joint, this paper presented a control attitude and kinematics and torque of the hip joint with power based neural network control. The CNN neural network uses input data only from the limb designed by the medical software, and is trained by different natural and artificially altered step patterns of healthy individuals. This type of network has been used for deep learning to realize adaptive speed control, dynamic and motion attitude, as well as prediction of force and torque performance. Detailed movement and torque tests were performed using MIMICS and ANATOMY AND PHYSIOLOGY software, and the obtained data were checked and varied by a…

Citation impact

511
total citations
FWCI
260.73
Percentile
100%
References
24
Citations per year

Authors

3

Topics & keywords

Keywords
  • Kinematics
  • Moment (physics)
  • Rotation (mathematics)
  • Pelvis
  • Joint (building)
  • Convolutional neural network
  • Computer science
  • Physical medicine and rehabilitation
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