Outputs (2)

A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers (2020)
Conference Proceeding
Day, C. R., Chadwick, E. K., & Blana, D. (2020). A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers. In 2020 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN48605.2020.9206772

Transhumeral amputation has a considerable detrimental effect on the amputee’s quality of life and independence. Previous work has already established the potential for exploiting proximal humerus myoelectric and kinematic signals for the effective c... Read More about A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers.

Digital Twin: Enabling Technologies, Challenges and Open Research (2020)
Journal Article
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020). Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access, 108952 - 108971. https://doi.org/10.1109/ACCESS.2020.2998358

Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry... Read More about Digital Twin: Enabling Technologies, Challenges and Open Research.