Advanced Rehabilitative Technology: Neural Interfaces and Devices

Advanced Rehabilitative Technology teaches readers how to: (i) acquire and process bio-signals using biosensors and acquisition devices; (ii) identify the human movement intention and decode the brain signal; (iii) design physiological and musculoskeletal models and establish the neural interfaces; and (iv) develop neural devices and control them efficiently using biological signals. If you are new to this field, this book clearly and concisely lays out the background, state of the art as well as the most recent work in this field. It takes a multidisciplinary theme between the engineering and medical field.

Advanced Rehabilitative Technology includes four sections to solve four key problems in neural interfaces and devices; (i) neuromuscular/brain signal processing; (ii) human motion and intention recognition; (iii) biomechanics modelling and interfaces; and (iv) neural devices and control for rehabilitation. Each chapter goes through a detailed description of the bio-mechatronic systems used and then the implementation and testing to show how it fulfils the needs of that specific area of rehabilitation. It details new neural interfaces and devices, some of which have never been published before in any journals or conferences. With this book, you will be able to get up to speed on the most recent and future advancements in bio-mechatronics engineering as well as in the rehabilitation field

The author team has over 20 years’ experience in neurological systems, bio-mechatronics and rehabilitation engineering; this book presents their insights into emerging technologies and developments that are being or will be utilized in biological systems and mechatronics for rehabilitative purposesGives a comprehensive background of biological interfaces and details of new advances in the fieldAddresses the challenges of rehabilitative applications in areas of bio-signal processing, bio-modelling, neural and muscular interface, and neural devices. Each chapter provides substantial background materials and relevant case studies to each subject

1. Introduction
2. State of the Art
3. Neuromuscular Signal Acquisition and Pre-Processing
4. EMG-Based Motion Recognition
5. Brain Signal Acquisition and Pre-Processing
6. EEG-Based Brain Intention Recognition
7. Neuromuscular Modelling
8. Neural Interfaces
9. Neural Devices
10. Conclusion