Wearable Sensing and Assistive Devices for Robotic Rehabilitation provides an overview of current research and developments in the field of innovative technologies for advanced wearable sensing and assistive devices in medical rehabilitation. The book presents a systematic investigation into the wearable acquisition and deep learning-based processing of biological signals and applications with wearable robotic devices. It provides fundamental bio-mechatronics engineering knowledge to analyze and design new wearable sensing and assistive devices.In addition, the book includes human wearable sensors design and development, biological signals acquisition and processing, brain-computer interface and neuromuscular interfaces, wearable exoskeleton and soft robotic devices, and human-centered interactive robot control. - Presents expertise from an authoring team with more than 20 years of experience working in neurological and robotic systems, bio-mechatronics, and rehabilitation engineering - Contains insights into emerging technologies and developments that are being, or will be, utilized in biological systems and mechatronics for rehabilitative purpose - Provides an all-in-one, comprehensive background on human wearable sensing and assistive devices, detailing new advances in the field - Addresses challenges for robotic rehabilitation applications in bio-signal sensing and processing, brain and muscular interfaces, and wearable robotic devices and control



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Wei Meng is currently a lecturer at the School of Information Engineering, Wuhan University of Technology. His research interests include robot-assisted rehabilitation, human-robot interaction, and iterative learning control. He has co-authored five books, published more than 80 academic journal and conference papers, and holds 22 patents.Li Ma is an associate professor at Wuhan University of Technology, China. From 2015 to 2016, he was a PhD exchange student in National Taiwan University, Taiwan and a joint training PhD student at UCLA, US, from 2016 to 2018. After that, he carried on one-year postdoctoral research fellow at University of Michigan, US. His research interest includes the biomedical signal processing, especially in brain monitoring during anaesthesia, brain modelling and brain-computer interfaces, and is now focusing on the brain inspired intelligence.Quan Liu is currently chair professor at the School of Information Engineering at Wuhan University of Technology. In the past five years, she authored more than 100 technical publications, proceedings, editorials, and books. She has directed more than 20 research projects. Her research interests include signal processing, embedded systems, and robots and electronics. Prof. Liu received two national awards and three provincial and ministerial awards. She was awarded as the "National Excellent Teacher in 2007. She is a Council Member of the Chinese Association of Electromagnetic Compatibility and the Hubei Institute of Electronics.Sheng Quan Xie is currently chair professor in robotics and autonomous systems at the Faculty of Engineering, University of Leeds. He has published seven books, 15 book chapters, and more than 300 international journal and conference papers. His current research interests include medical and rehabilitation robots and advanced robot control. Professor Xie was elected a Fellow of The Institution of Professional Engineers New Zealand in 2016. He has also served as a Technical Editor of the IEEE/ASME TRANSACTIONS ON MECHATRONICS.Jie Zuo received the Ph.D. degree in information engineering from Wuhan University of Technology, Wuhan, China, in 2022. She is currently working as a Lecturer at Wuhan University of Technology. From 2022 to 2024, she was a postdoctoral researcher in the School of Artificial Intelligence and Automation at Huazhong University of Science and Technology. Her research interests include robotic design, modelling and control strategies, rehabilitation bio-mechatronics.

Titel
Wearable Sensing and Assistive Devices for Robotic Rehabilitation
EAN
9780443404641
Format
E-Book (epub)
Veröffentlichung
02.04.2026
Digitaler Kopierschutz
Wasserzeichen
Dateigrösse
51.52 MB
Anzahl Seiten
350