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The study of technology and its implications in the medical field has become an increasingly crucial area of research. By integrating technological innovations into clinical practices, patients can receive improved diagnoses and treatments, as well as faster and safer recoveries.
Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation is an authoritative reference source for the latest scholarly research on the use of computer-assisted rehabilitation methods for disabled patients. Highlighting the application of robots, sensors, and virtual environments, this book is ideally designed for graduate students, engineers, technicians, and company administrators interested in the incorporation of auto-training methods in patient recovery.
- Published on: 2016-01-07
- Original language: English
- Number of items: 1
- Dimensions: 11.02" h x .94" w x 8.50" l, 2.71 pounds
- Binding: Hardcover
- 383 pages
Review
The book has a good flow of contents, starting from more general and simple to more specific and complex topics. Contents are updated and represent the latest research trends in the field of rehabilitation through virtual reality and robotics. [...] Highly Recommended. This book is an important tool for computer scientists and clinicians involved in disability rehabilitation through virtual reality and robotics since its updated and focus on emerging topics in the field. --Ana Lúcia Faria, Neuropsychologist, Madeira Interactive Technologies Institute
I consider this book to be one of the most outstanding examples in discussing neurologic, neuropsychological and neurorehabilitation advances; one that will bring realistic improvements to this unique research field. --Andreia Polido de Almeida, Neuropsychologist, Instituto Superior da Maia, Porto, Portugal
Illustrates the advantages of virtual reality in the rehabilitation process, establishing the history and evolution of the virtual reality systems. Recommended for psychiatrists, physiotherapists, occupational therapists, psychologists and neuropsychologists. --Sara Silva, Psychologist, Centro de Reabilitação do Norte, Portugal
About the Author
Dr. Fei Hu is currently a professor in the Department of Electrical and Computer Engineering at the University of Alabama, Tuscaloosa, Alabama, USA. He obtained his Ph.D. degrees at Tongji University (Shanghai, China) in the field of Signal Processing (in 1999), and at Clarkson University (New York, USA) in Electrical and Computer Engineering (in 2002). He has published over 200 journal/conference papers and books. Dr. Hu's research has been supported by U.S. National Science Foundation, Cisco, Sprint, and other sources. His research expertise can be summarized as 3S: Security, Signals, Sensors: (1) Security: This is about how to overcome different cyber attacks in a complex wireless or wired network. Recently he focuses on cyber-physical system security and medical security issues. (2) Signals: This mainly refers to intelligent signal processing, that is, using machine learning algorithms to process sensing signals in a smart way in order to extract patterns (i.e., pattern recognition). (3) Sensors: This includes micro-sensor design and wireless sensor networking issues.
Dr. Jiang Lu is currently an assistant professor in the Department of Computer Engineering at University of Houston Clear Lake, Houston, Texas, USA. He obtained his Ph.D. degrees at the University of Alabama (Tuscaloosa, AL, USA) in the field of Electrical and Computer Engineering. He received Bachelor of Science degree from Shanghai Maritime University in China and Master of Science degree in Electrical and Computer Engineering from University of Florida. Dr. Lus research interests are in the areas of intelligent sensor systems, biomedical devices, tele-healthcare, wireless communication, signal/image processing, machine learning and embedded system designs.
Ting Zhang received the B.E. degree in computer engineering from Tianjing University, Tianjing, China in 2008, and the M.S. degree in computer science from University of Texas at Brownsville, Brownsville, TX in 2011. She is currently working toward the Ph.D. degree in Electrical and Computer Engineering at The University of Alabama, Tuscaloosa, AL. Her research interests include machine learning and pattern recognition, intelligent sensor systems, tele-healthcare, and mobile computing.
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