2023 - Research.com Electronics and Electrical Engineering in United Kingdom Leader Award
Etienne Burdet spends much of his time researching Control theory, Motor learning, Simulation, Control engineering and Actuator. His Control theory study combines topics from a wide range of disciplines, such as Electrical impedance, Impedance control and Stiffness. His study in Impedance control is interdisciplinary in nature, drawing from both Inverse dynamics and Motor control.
His Motor learning research is multidisciplinary, incorporating elements of Interpersonal relationship, Robustness, Artificial intelligence and Computer vision. The Control theory research Etienne Burdet does as part of his general Control engineering study is frequently linked to other disciplines of science, such as Dynamics, therefore creating a link between diverse domains of science. His work deals with themes such as Robot, Interventional magnetic resonance imaging, Haptic technology and Mechatronics, which intersect with Actuator.
Etienne Burdet mostly deals with Simulation, Artificial intelligence, Robot, Control theory and Haptic technology. His biological study spans a wide range of topics, including Rehabilitation, Mechanism, Motor control, Wheelchair and Torque. His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Computer vision.
His Robot research is multidisciplinary, incorporating perspectives in Electrical impedance and Human–computer interaction. His studies deal with areas such as Control engineering and Impedance control as well as Control theory. As a part of the same scientific family, Etienne Burdet mostly works in the field of Control engineering, focusing on Actuator and, on occasion, Clutch.
His primary scientific interests are in Robot, Physical medicine and rehabilitation, Simulation, Artificial intelligence and Human–computer interaction. The various areas that he examines in his Robot study include Control theory, Haptic technology and Trajectory. The study incorporates disciplines such as Control engineering and Electrical impedance in addition to Trajectory.
He interconnects Rehabilitation, Neurorehabilitation, Lower limb and Motor learning in the investigation of issues within Physical medicine and rehabilitation. His research in Simulation intersects with topics in Mechanical impedance, Torque, Robotic arm, User experience design and Robot kinematics. His Artificial intelligence research includes elements of Exoskeleton and Computer vision.
His main research concerns Artificial intelligence, Physical medicine and rehabilitation, Robotics, Robot and Rehabilitation. His work focuses on many connections between Artificial intelligence and other disciplines, such as Exoskeleton, that overlap with his field of interest in Computer vision, Control and Orientation. His Physical medicine and rehabilitation study combines topics in areas such as Neurorehabilitation and Motor learning.
As part of the same scientific family, Etienne Burdet usually focuses on Robotics, concentrating on Simulation and intersecting with Surgical instrument, Teleoperation and Grip force. His Robot research integrates issues from Orthotic device, Control theory and Human–computer interaction. Etienne Burdet studied Human–computer interaction and Haptic technology that intersect with Key, Movement and Iterative learning control.
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The central nervous system stabilizes unstable dynamics by learning optimal impedance.
Etienne Burdet;Rieko Osu;David W. Franklin;Theodore E. Milner.
Nature (2001)
Variable impedance actuators: A review
B. Vanderborght;A. Albu-Schaeffer;A. Bicchi;A. Bicchi;E. Burdet.
Robotics and Autonomous Systems (2013)
A Brain Controlled Wheelchair to Navigate in Familiar Environments
B Rebsamen;Cuntai Guan;Haihong Zhang;Chuanchu Wang.
international conference of the ieee engineering in medicine and biology society (2010)
Adaptation to Stable and Unstable Dynamics Achieved By Combined Impedance Control and Inverse Dynamics Model
David W. Franklin;Rieko Osu;Etienne Burdet;Mitsuo Kawato.
Journal of Neurophysiology (2003)
Fabrication of 3D chitosan–hydroxyapatite scaffolds using a robotic dispensing system
T.H. Ang;F.S.A. Sultana;Dietmar Hutmacher;Yoke San Wong.
Materials Science and Engineering: C (2002)
CNS learns stable, accurate, and efficient movements using a simple algorithm.
David W Franklin;Etienne Burdet;Etienne Burdet;Keng Peng Tee;Keng Peng Tee;Rieko Osu.
The Journal of Neuroscience (2008)
Human-Like Adaptation of Force and Impedance in Stable and Unstable Interactions
Chenguang Yang;G. Ganesh;S. Haddadin;S. Parusel.
IEEE Transactions on Robotics (2011)
On the analysis of movement smoothness.
Sivakumar Balasubramanian;Alejandro Melendez-Calderon;Agnes Roby-Brami;Etienne Burdet.
Journal of Neuroengineering and Rehabilitation (2015)
Controlling a Wheelchair Indoors Using Thought
B. Rebsamen;C.L. Teo;Q. Zeng;M.H. Ang.
IEEE Intelligent Systems (2007)
A Robust and Sensitive Metric for Quantifying Movement Smoothness
S. Balasubramanian;A. Melendez-Calderon;E. Burdet.
IEEE Transactions on Biomedical Engineering (2012)
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