7 citations · 21 across the 6 of their papers we have counts for
7 papers
Towards AI-controlled FES-restoration of movements: Learning cycling stimulation pattern with reinforcement learning
Nat Wannawas, A. Aldo Faisal
Functional electrical stimulation (FES) has been increasingly integrated with other rehabilitation devices, including robots. FES cycling is one of the common FES applications in r…
Neuromuscular Reinforcement Learning to Actuate Human Limbs through FES
Nat Wannawas, Ali Shafti, A. Aldo Faisal
Functional Electrical Stimulation (FES) is a technique to evoke muscle contraction through low-energy electrical signals. FES can animate paralysed limbs. Yet, an open challenge re…
The role of haptic communication in dyadic collaborative object manipulation tasks
Yiming Liu, Raz Leib, William Dudley +3
Intuitive and efficient physical human-robot collaboration relies on the mutual observability of the human and the robot, i.e. the two entities being able to interpret each other's…
The Response Shift Paradigm to Quantify Human Trust in AI Recommendations
Ali Shafti, Victoria Derks, Hannah Kay +1
Explainability, interpretability and how much they affect human trust in AI systems are ultimately problems of human cognition as much as machine learning, yet the effectiveness of…
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup +18
Transfer learning and meta-learning offer some of the most promising avenues to unlock the scalability of healthcare and consumer technologies driven by biosignal data. This is bec…
Real-World Human-Robot Collaborative Reinforcement Learning
Ali Shafti, Jonas Tjomsland, William Dudley +1
The intuitive collaboration of humans and intelligent robots (embodied AI) in the real-world is an essential objective for many desirable applications of robotics. Whilst there is…