J. McPhee

Simulation of Energy Regeneration in Human Locomotion for Efficient Exoskeleton Actuation

This study simulates energy regeneration in human locomotion to improve exoskeleton efficiency, finding that slower speeds and decline slopes significantly extend battery life.

Environment Classification for Robotic Leg Prostheses and Exoskeletons using Deep Convolutional Neural Networks

This paper develops an environment classification system for robotic leg prostheses and exoskeletons using deep convolutional neural networks, achieving accurate and efficient real-time predictions of walking environments.

Computer Vision and Deep Learning for Environment-Adaptive Control of Robotic Lower-Limb Exoskeletons

The paper develops an environment recognition system for robotic exoskeletons using computer vision and deep learning, achieving 73% classification accuracy on a new dataset.

ExoNet Database: Wearable Camera Images of Human Locomotion Environments

ExoNet provides a large-scale, open-source database of wearable camera images for human locomotion environments to improve image classification algorithms for exoskeletons and prostheses.

Simulation of Stand-to-Sit Biomechanics for Design of Lower-Limb Exoskeletons and Prostheses with Energy Regeneration

This study simulates stand-to-sit biomechanics to estimate biomechanical energy available for electrical regeneration in lower-limb exoskeletons and prostheses.