Human-Machine Interfaces in Medical Robotics

Human-Machine Interfaces in Medical Robotics presents essential and advanced information on developing intuitive human-machine interfaces (HMI) for robotic surgery and rehabilitation. This book provides extensive coverage of multidisciplinary information needed to develop efficient HMI, discussing core technologies of the field, including hand-free control strategies, sensory feedback, data-driven approaches, human-robot shared control, autonomous control, human motor adaption, training, and learning.

Arranged in three parts, including interfaces in medical robotics, intelligent machines, and human users, this book provides potential solutions to open questions like what the optimal interface and efficient interaction mode is to facilitate a surgeon’s operation, a patient’s motor control, or human augmentation.

• Provides a comprehensive review of human-machine interfaces in the medical robotics field and summarizes their core design principles, methods and evaluations
• Presents updated technology coverage in multiple disciplines
• Explores how human users adapt to and learn efficiently from the interface and how machines become more intelligent to assist humans

Yanpei Huang is a lecturer at the Department of Engineering and Design, University of Sussex, UK. Before joining Sussex, she was a post-doctoral researcher in the Human Robotics Group, at the Department of Bioengineering, Imperial College London, U.K, where she investigated movement augmentation strategies in Virtual Reality. Yanpei Huang completed her Ph.D. study at Nanyang Technological University, Singapore, with a focus on the development of intuitive human-machine interfaces for robotic surgery. Prior to the Ph.D. study, she received the M.Sc. degree in Manufacturing Systems & Engineering from Nanyang Technological University, Singapore. Her current research interests include human–machine interaction and medical robotics.

Ziwei Wang is a lecturer in Robotics and the Director of Advanced Robotic Teleoperation Lab, at the School of Engineering, Lancaster University, U.K. He received the PhD from the Department of Automation, Tsinghua University, China. During the period of 2020 and 2022, he was a research associate with the Human Robotics Group, the Department of Bioengineering, Imperial College London, U.K. His research interests focus on autonomous robot, fuzzy control, human-robot shared control and computational intelligence for medical applications, aiming at enhancing human sensorimotor capability and overall robotic system performance.

Yongkun Zhao is a PhD candidate at the Faculty of Engineering's Department of Bioengineering, Imperial College London, United Kingdom.

Xiaoxiao Cheng is a Lecturer in Engineering Systems for Robotics at the University of Manchester. Before joining in the University of Manchester, he worked as a Research Associate at Imperial College London from 2020 to 2023 and a Research Fellow at Stanford University from 2019 to 2020. He received his Ph.D. degree in Electrical and Electronic Engineering from The University of Melbourne in 2019, M. Phil. degree in Mechanical Engineering from Tsinghua University in 2014, and B. Eng. degree in Mechanical Engineering from Beijing Institute of Technology in 2011. His research focuses on developing intelligent autonomous systems and human-machine interfaces by considering and integrating factors from robotics, control, artificial intelligence, and neuroscience.

Wenjie Lai earned her Ph.D. in the field of flexible endoscopic surgical robotics from Nanyang Technological University (NTU), Singapore, in 2021. She completed her undergraduate studies at NTU in 2015, graduating with the first-class honour in Mechatronics under the SM3 scholarship.

Currently, she works as a research fellow at CREATE, NTU, in the Smart Grippers for Soft Robotics (SGSR) program. After completing her Ph.D., Dr. Lai ventured into the industry at Ronovo Surgical, a Shanghai-based startup specializing in laparoscopic robots. There, she immersed herself in the development of performance metrics for robot-assisted Minimally Invasive Surgery (MIS) instruments, gaining valuable insights into real-world challenges and industry demands.

Dr. Lai has made several contributions to academia, with publications in prestigious journals such as TMECH, RAL, and ABME, and presentations at top-tier international conferences like ICRA. She actively serves as a reviewer for journals such as Soft Robotics, TMECH, and TIM, as well as conferences like IROS and Robosoft. She holds multiple patents in the field of sensors, surgical robots, and soft robots, including one granted in both the US and China. Dr. Lai's research interests include surgical robotics, soft robotics, haptic feedback, and sensor development.