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The book reports on advanced topics in the areas of neurorehabilitation research and practice. It focuses on new methods for interfacing the human nervous system with electronic and mechatronic systems to restore or compensate impaired neural functions. Importantly, the book merges different perspectives, such as the clinical, neurophysiological, and bioengineering ones, to promote, feed and encourage collaborations between clinicians, neuroscientists and engineers. Based on the 2020 International Conference on Neurorehabilitation (ICNR 2020) held online on October 13-16, 2020, this book covers various aspects of neurorehabilitation research and practice, including new insights into biomechanics, brain physiology, neuroplasticity, and brain damages and diseases, as well as innovative methods and technologies for studying and/or recovering brain function, from data mining to interface technologies and neuroprosthetics. In this way, it offers a concise, yet comprehensive reference guide to neurosurgeons, rehabilitation physicians, neurologists, and bioengineers. Moreover, by highlighting current challenges in understanding brain diseases as well as in the available technologies and their implementation, the book is also expected to foster new collaborations between the different groups, thus stimulating new ideas and research directions.

Restoring human motor and cognitive function has been a fascinating research area during the last century. Interfacing the human nervous system with electro-mechanical rehabilitation machines is facing its crucial passage from research to clinical practice, enhancing the potentiality of therapists, clinicians and researchers to rehabilitate, diagnose and generate knowledge. The 2012 International Conference on Neurorehabilitation (ICNR2012) brings together researchers and students from the fields of Clinical Rehabilitation, Applied Neurophysiology and Biomedical Engineering, covering a wide range of research topics: · Clinical Impact of Technology · Brain-Computer Interface in Rehabilitation · Neuromotor & Neurosensory modeling and processing · Biomechanics in Rehabilitation · Neural Prostheses in Rehabilitation · Neuro-Robotics in Rehabilitation · Neuromodulation This Proceedings book includes general contributions (2-page extended abstracts) from oral and poster sessions, as well as from special sessions. A section is also dedicated to pre-post conference workshops, including invited contributions from internationally recognized researchers. A selection of most relevant papers have been considered for publication in international journals (e.g. JNER, JACCES, ...)., therefore they will appear soon in their extended versions in Special Issues. These Proceedings also contain brief descriptions of keynote lectures from invited world-class professors, and a number of thematic round tables covering technological and institutional issues.

Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.

This book reports on the latest technological and clinical advances in the field of neurorehabilitation. It is, however, much more than a conventional survey of the state-of-the-art in neurorehabilitation technologies and therapies. It was formed on the basis of a week of lively discussions between curious PhD students and leading research experts during the summer school on neurorehabilitation (SSNR2012), September 16-21 in Nuévalos, Zaragoza (Spain). Its unconventional format makes it a perfect guide for all PhD students, researchers and professionals interested in gaining a multidisciplinary perspective on current and future neurorehabilitation scenarios. The book covers various aspects of neurorehabilitation research and practice, organized into different parts. The first part discusses a selection of common impairments affecting brain function, such as stroke, cerebral palsy and Parkinson’s disease; the second deals with both spinal cord and brain plasticity. The third part covers the most recent rehabilitation and diagnostics technologies, including robotics, neuroprostheses, brain-machine interfaces and electromyography systems. Practical examples and case studies related to the application of some of the latest techniques in realistic clinical scenarios are covered in the fourth part.

Neurointelligence techniques play a key role in building general artificial intelligence systems. Some researchers and engineers have tried to design novel bio-inspired algorithms and hardware by mimicking the working principles of biological nervous systems. Benefiting from the progress in representational learning, neuroscience, and computational hardware, bio-inspired research has greatly contributed to the development of neurointelligence. Currently, advanced bio-inspired methods have been widely applied in robotics, visual scene understanding, medical image analysis, human-machine interaction and so on. Moreover, neurointelligence covers interdisciplinary topics with neuroscience, robotics, artificial intelligence, cognitive science, machine learning, and pattern recognition. This research topic is intended to provide a better understanding of the opportunities, challenges, and promising future directions for neurointelligence.