Bio-inspired Motor Control Strategies for Redundant and Flexible Manipulator with Application to Tooling Tasks (eBook)

This book presents a multi-disciplinary view of all aspects of rehabilitation robotics and non-invasive surgery, ideal for anyone new to the field. It includes perspectives from both engineers and clinicians. For skilled researchers and clinicians, it also summarizes current robot technologies and their application to various pathologies. The book will help the readers to develop the know-how and expertise necessary to guide those seeking a comprehensive understanding of this topic through their use of several commercial devices for robotic rehabilitation. The book targets the implementation of efficient robot strategies to facilitate the re-acquisition of motor skills. This technology incorporates the outcomes of behavioral studies on motor learning and its neural correlates into the design, implementation, and validation of robot agents that behave as optimal trainers, efficiently exploiting the structure and plasticity of the human sensorimotor systems.

Gia Hoang Phan holds Ph.D. and is Senior Postdoctoral Fellow in Robotics. He received his Ph.D. from the School of Mechanical and Aerospace Engineering, Nanyang Technological University (NTU), Singapore.  Broadly, his research interests include investigating methods for rehabilitation and assessment of sensory-motor functions post neurological injuries, understanding and quantifying human strategies during skilled manipulation tasks, and its translation into robotics. He has more than ten years of academic experience in a robotics application, including the analysis of cable-driven robotics, designing and characterization of an instrumented tool, impedance-force control, redundant manipulators, variable stiffness devices, and motion tracker. He used to work as Research Fellow in the production and R&D of Aviation & Aerospace at Rolls-Royce, Singapore, where he programmed control algorithms for the compliant robot (KUKA robot) to operate the finesse finishing tasks on Fan Blade of Turbine engine. In addition, he worked as Postdoctoral in the Department of Mechanical and Aerospace Engineering, Monash University, Australia, where he led projects cooperated with the Royal Melbourne Hospital using medical robotics application for surgery of liver tumors. Currently, he has also worked as Tech Consultant for start-ups and business firms.   

 

Nguyen Ho Quang holds Ph.D. and is currently Associate Dean and Head of Mechatronics engineering department, Faculty of Technology and Engineering at Thu Dau Mot University (TDMU). He holds a bachelor's degree in Mechanical Engineering from University of Science and Technology, Da Nang University, Vietnam, in 2005. He obtained his M.Sc. degree in Mechanical Engineering from the Thai Nguyen University of Technology, Vietnam, in 2010. In 2017, he received his Ph.D. degree in Biomechanics and Computational Mechanics from University of Technology of Compiègne (UTC), Sorbonnes University, France. And he has also completed postdoctoral fellowships at the Biomechanics and Bioengineering Laboratory, UTC, France. His main research interests relate to computational biomechanics and clinical applications including biomechanics of the musculoskeletal system, patient-specific biomechanical modelling derived from medical images, and rehabilitation engineering.

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This book presents a multi-disciplinary view of all aspects of rehabilitation robotics and non-invasive surgery, ideal for anyone new to the field. It includes perspectives from both engineers and clinicians. For skilled researchers and clinicians, it also summarizes current robot technologies and their application to various pathologies. The book will help the readers to develop the know-how and expertise necessary to guide those seeking a comprehensive understanding of this topic through their use of several commercial devices for robotic rehabilitation. The book targets the implementation of efficient robot strategies to facilitate the re-acquisition of motor skills. This technology incorporates the outcomes of behavioral studies on motor learning and its neural correlates into the design, implementation, and validation of robot agents that behave as optimal trainers, efficiently exploiting the structure and plasticity of the human sensorimotor systems.