Shane Xie, PhD, Professor
School of Electronic and Electrical Engineering, University of Leeds, UK
Title: Innovative Robotic Technology and Artificial Intelligence for
the Future of Healthcare
Abstract
Stroke and neurological diseases have significant impact on our society, this talk will discuss the key societal challenges, robotic technologies for delivering effective care and opportunities for the healthcare industry. The keynote will cover the recent development of robotics for stroke rehabilitation, the research gaps and the need for new technologies in neuroscience, robotics and artificial intelligence. The talk will introduce a EPSRC-funded project on intelligent reconfigurable exoskeletons tailored to meet patients’ needs, deliver effective diagnosis and personalised treatment, and monitored remotely by rehabilitation therapists. The talk will also briefly introduce the Leeds Centre for Assistive/Rehabilitation Robotics and our work on ankle robot, gait exoskeleton, gait upper limb bilaterial robot, neuromuscular and brain computer interfaces. The focus is on the enabling technologies for those whose strength and coordination have been affected by amputation, stroke, spinal cord injury, cerebral palsy and ageing.
Biography
Prof Shane (Sheng Q) Xie, Ph.D., FIPENZ, is the Chair of Robotics and Autonomous Systems and Director of the Rehabilitation Robotics Lab at the University of Leeds, and he was the Director of the Rehabilitation and Medical Robotics Centre at the University of Auckland, New Zealand (NZ, 2002-2016). He has >28 years of research experience in healthcare robotics and exoskeletons. He has published > 400 refereed papers and 8 books in rehabilitation exoskeleton design and control, neuromuscular modelling, and advanced human-robot interaction. He has supervised >15 postdocs, 62 PhDs and 80 MEs in his team with funding of >£27M from five countries since 2003. His team has invented three award-winning rehabilitation exoskeletons. He is an expert in control of exoskeletons, i.e. impedance control, adaptive control, sliding mode control, and iterative learning control strategies. He has received many distinguished awards including the New Zealand Science Challenge Award, the David Bensted Fellowship Award, and the AMP Invention Award. He is an elected Fellow of the Institute of Professional Engineers of New Zealand and the Technical Editor for IEEE/ASME Transaction on Mechatronics.