IMU-BASED CLASSIFICATION OF LOCOMOTION MODES, TRANSITIONS, AND GAIT PHASES WITH CONVOLUTIONAL RECURRENT NEURAL NETWORKS

IMU-Based Classification of Locomotion Modes, Transitions, and Gait Phases with Convolutional Recurrent Neural Networks

This paper focuses on the classification of seven locomotion modes (sitting, standing, level ground walking, ramp ascent and descent, stair ascent and descent), the transitions among these modes, and the gait phases within each mode, by only using data in the frequency domain from one or two inertial measurement units.Different deep neural network

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Intelligent computing technique to analyze the two-phase flow of dusty trihybrid nanofluid with Cattaneo-Christov heat flux model using Levenberg-Marquardt Neural-Networks

This study examines the characteristics french wrap plus of activation energy on the two-phase flow of a tri-hybrid nanofluid with variable thermal conductivity, viscous dissipation, and NHCMBM using a stochastic-based Levenberg-Marquardt backpropagated neural network (LMB-NN).The Darcy Forchheimer porous media characteristics is included in the mo

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