Flexible Robotics in Medicine: A Design Journey of Motion Generation Mechanisms and Biorobotic System Development provides a resource of knowledge and successful prototypes regarding flexible robots in medicine. With specialists in the medical field increasingly utilizing robotics in medical procedures, it is vital to improve current knowledge regarding technologies available. This book covers the background, medical requirements, biomedical engineering principles, and new research on soft robots, including general flexible robotic systems, design specifications, design rationale, fabrication, verification experiments, actuators and sensors in flexible medical robotic systems.
Presenting several projects as examples, the authors also discuss the pipeline to develop a medical robotic system, including important milestones such as involved regulations, device classifications and medical standards.
Hongliang Ren is currently an assistant professor and leading a research group on medical mechatronics in the Biomedical Engineering Department of National University of Singapore (NUS). He is an affiliated Principal Investigator for the Singapore Institute of Neurotechnology (SINAPSE) and Advanced Robotics Center at National University of Singapore. Dr. Ren received his PhD in Electronic Engineering (Specialized in Biomedical Engineering) from The Chinese University of Hong Kong (CUHK) in 2008. After his graduation, he worked as a Research Fellow in the Laboratory for Computational Sensing and Robotics (LCSR) and the Engineering Center for Computer-Integrated Surgical Systems and Technology (ERC-CISST), Department of Biomedical Engineering and Department of Computer Science, The Johns Hopkins University, Baltimore, MD, USA, from 2008 to 2010. In 2010, he joined the Pediatric Cardiac Biorobotics Lab, Department of Cardiovascular Surgery, Children's Hospital Boston & Harvard Medical School, USA, for investigating the beating heart robotic surgery system. Prior to joining NUS, he also worked in 2012 on a collaborative computer integrated surgery project, at the Surgical Innovation Institute of Children's National Medical Center, USA. His main areas of interest include Biomedical Mechatronics, Computer-Integrated Surgery, and Robotics in Medicine.
Dr. Ren's expertise includes Biorobotics & Intelligent Control, particularly the key challenges of flexible continuum compliant cooperative and cognitive robotics, haptics, and sensing and control in constrained human-interactive environments such as in surgeries. Representing a major paradigm shift from open surgery, minimally invasive surgery (MIS) assisted by robotics and sensing is emerging by accessing the surgical targets via either keyholes or natural orifices. It is challenging to accomplish delicate manipulations due to the constraints imposed by the mode of access, confined workspace, complicated surgical structures and the limited available technologies, particularly in terms of endoluminal curvilinear targeting and curvilinear guidance. Addressing the aforementioned challenges and aiming at the next generation of intelligent and flexible minimally invasive robots, he focuses on key biorobotics research in compliant robotic system development, modeling & control, flexible sensing, human-robot interaction and intelligent navigation, tackling fundamental and technical challenges mainly in the context of medical applications.
Dr. Ren has published more than 80 peer-reviewed papers in high-ranking journals and 80 top-tier international conference papers and won a number of awards in his area including the NUS Young Investigator Award, EMedic Global Gold Medal, Best Paper Awards in IEEE RCAR 2016, IEEE CCECE 2015, IEEE ROBIO 2013, IEEE Cyber 2014, and best paper finalists for ICVS2017, CSCWD 2016, ICMA 2016, IEEE ROBIO 2012 and 2013 among others. His supervised FYP students won the BES 2016 design gold award, IEEE RCAR 2016 best student paper award, and NUS FoE 28th Innovation and Research Award and Gold awards from Biomedical engineering Society. The H-index (Google Scholar) of Dr Ren's publication profile is 22 with 1736 citations and is expected to further increase in the future.
