Pervasive Computing in Healthcare

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· CRC Press
電子書
336
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With skyrocketing costs due to the increase in the elderly population, a rapid increase in lifestyle-related and chronic diseases, demand for new medical treatments and technologies, and a shortage in the number of available clinicians, nurses, and other caregivers, the challenges facing the healthcare industry seem insurmountable. However, by transforming the current model into a more distributed and highly responsive healthcare processing model, patients can take control of their own health in the form of wellness management, preventive care, and proactive intervention.

Pioneering the concepts of this newly emerging field, Pervasive Computing in Healthcare provides an introduction to and is the first known comprehensive resource on the application of pervasive computing in healthcare. The book begins with an overview of healthcare, diseases, disabilities, and computer science principles. It describes challenges in using computers in large, modern hospitals, how current software and hardware technology is evolving to meet these challenges, and new pervasive technologies for people with cognitive disabilities. Identifying the main usage models and applications for mobile and personal health, the book explores sensors and wearable technologies. It also examines current research in assistive technologies, challenges associated with human factors and the usability of healthcare systems, and methods for technology innovation. The book concludes by presenting user evaluations with a special focus on real-world deployment and assessment of the technology.

Pervasive healthcare is an exciting emerging research area that is bound to play an important role in an increasingly aging society. Providing a solid foundation on which current and future researchers and practitioners can build and use to further their endeavours, Pervasive Computing in Healthcare addresses a set of related technologies and concepts that help integrate healthcare more seamlessly.

關於作者

Jakob E. Bardram, Alex Mihailidis, Dadong Wan

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