Preface

Abstract

Since the first edition of this book, the field of Body Sensor Networks (BSNs) has advanced rapidly. The original motivation of BSN was to harness allied technologies that underpin the development of pervasive sensing for healthcare, wellbeing, sports and other applications that require “ubiquitous” and “pervasive” monitoring of physical, physiological, and biochemical parameters in any environment without activity restriction and behaviour modification. The ultimate aim of BSN is therefore to provide a truly personalised monitoring platform that is pervasive, intelligent and context-aware, yet “invisible”, with applications ranging from managing patients with chronic disease and care for the elderly, to general well-being monitoring and performance evaluation in sports. To ensure its widespread use, there are many technical challenges that need to be tackled. These include the need for better sensor design, MEMS integration, biocompatibility, power source miniaturisation, low power wireless transmission, context awareness, secure data transfer and integration with smart therapeutic systems. In this second edition of the book, we have updated the chapters with the latest developments in the field, addressing sensor design, micro-electronics and information processing aspects of the system. Since its inception, the development of BSN has been focussed on both wearable and implantable sensors. In the last few decades, we have seen rapid advances in both chemical and biosensor developments. The emergence of new biological sensing modalities is fundamentally changing the way we apply biomeasurements in vivo. In terms of implantable sensing, many of the issues associated with the extension of biosensor technology from in vitro to in vivo applications have long been appreciated, and a number of practical issues are addressed in this book. In a BSN with limited bandwidth and power constraints, the conventional method of data acquisition and analogue-todigital data conversion with signal processing taking place after transmission is no longer optimal. A BSN represents a prime candidate for bio-inspired local processing to take place at the sensor front-end before transmission. This processing