52 citations · 101 across the 15 of their papers we have counts for
18 papers
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…
MIDAS: Deep learning human action intention prediction from natural eye movement patterns
Paul Festor, Ali Shafti, Alex Harston +3
Eye movements have long been studied as a window into the attentional mechanisms of the human brain and made accessible as novelty style human-machine interfaces. However, not ever…
I am Robot: Neuromuscular Reinforcement Learning to Actuate Human Limbs through Functional Electrical Stimulation
Nat Wannawas, Ali Shafti, A. Aldo Faisal
Human movement disorders or paralysis lead to the loss of control of muscle activation and thus motor control. Functional Electrical Stimulation (FES) is an established and safe te…
Gaze-contingent decoding of human navigation intention on an autonomous wheelchair platform
Mahendran Subramanian, Suhyung Park, Pavel Orlov +2
We have pioneered the Where-You-Look-Is Where-You-Go approach to controlling mobility platforms by decoding how the user looks at the environment to understand where they want to n…