Body Sensor Networking, Design and Algorithms

 
 
Wiley (Verlag)
  • 1. Auflage
  • |
  • erschienen am 30. April 2020
  • |
  • 416 Seiten
 
E-Book | ePUB mit Adobe DRM | Systemvoraussetzungen
978-1-119-39001-5 (ISBN)
 
A complete guide to the state of the art theoretical and manufacturing developments of body sensor network, design, and algorithms

In Body Sensor Networking, Design, and Algorithms, professionals in the field of Biomedical Engineering and e-health get an in-depth look at advancements, changes, and developments. When it comes to advances in the industry, the text looks at cooperative networks, noninvasive and implantable sensor microelectronics, wireless sensor networks, platforms, and optimization--to name a few.

Each chapter provides essential information needed to understand the current landscape of technology and mechanical developments. It covers subjects including Physiological Sensors, Sleep Stage Classification, Contactless Monitoring, and much more.

Among the many topics covered, the text also includes additions such as:

* Over 120 figures, charts, and tables to assist with the understanding of complex topics

* Design examples and detailed experimental works

* A companion website featuring MATLAB and selected data sets

Additionally, readers will learn about wearable and implantable devices, invasive and noninvasive monitoring, biocompatibility, and the tools and platforms for long-term, low-power deployment of wireless communications. It's an essential resource for understanding the applications and practical implementation of BSN when it comes to elderly care, how to manage patients with chronic illnesses and diseases, and use cases for rehabilitation.
weitere Ausgaben werden ermittelt
Saeid Sanei is a Professor of Biomedical Signal Processing and Machine Learning at Nottingham Trent University and a Visiting Professor to Imperial College London, in the United Kingdom. His major contributions in advanced signal processing techniques such as tensor factorization, cooperative networking, compressive sensing, statistical signal processing, and subspace analysis have applications in physiological signal processing and sensor networks as explored in his three published monograms and over 400 publications.

Delaram Jarchi is currently a Lecturer at Essex University. She has been working intensively on sensor networks design and algorithms levels. Her research is focused on designing new algorithms and validation of commercial wearable sensors for robust estimation of physiological parameters such as heart rate, respiratory rate and blood oxygen saturation levels in very unobtrusive ways. She is a senior member of IEEE since 2018.

Anthony G. Constantinides is a Professor at Imperial College of London UK. He is an IEEE acknowledged pioneer in signal processing with research interests that span a wide range of applications of the area. Amongst these and relevant to the present book are included topics such as data analytics, acquisition, sensing, transmission, and compression.

1
Introduction


1.1 History of Wearable Technology


Earlier in history, it would take hundreds of years between breakthroughs such as eyeglasses being developed in 1286 and the abacus ring being manufactured in 1600. Today, new wearable tech innovations happen on a monthly basis, if not weekly. In the last 10?years, we have had the Google Glass, Fitbit, Oculus Rift, and countless others.

The Nuremberg egg manufactured in 1510 by Peter Henlein was one of the early portable mechanical timekeeping devices (like a watch) which had a chain to hang over the neck. An air-conditioned top hat was a wearable designed by a Victorian in the nineteenth century. In 1890, a lighting company in New York used to send girls with wearable lights onto the performance stage and to light up houses during ceremonies. In the1960s, the wearers of roulette shoes, created by Edward Thorp and Claude Shannon, used to observe the rotations of the roulette ball, tap the shoe accordingly, and then receive a vibration telling them which number to bet on. In 1963, a small portable TV screen was worn as a glass. The aviator Alberto Santos-Dumont pioneered the use of the wristwatch in 1904 as it allowed him to have his hands free while flying. This also led people to start using wristwatches. Calculator watches came onto market in 1975 and the first low-cost Walkman stereo was offered by Sony in 1979. In the 1990s, interest in the Internet of Things (IoT) started to rise. In December 1994, Steve Mann, a Canadian researcher, developed the wearable wireless Webcam. Despite its bulk, it paved the way for future IoT technologies. This required advances in artificial intelligence, which started to flourish in the 2000s.

The Sony Walkman was a clear commercial success. The Walkman and subsequent Sony Discman helped the company become an entertainment powerhouse. Over 400?million Walkman portable music players have been sold with about 200?million of those being cassette players.

However, not all products launched with a fanfare are destined for success. The commercial potential of many wearable technologies introduced in recent years are not always predictable or even achieved.

Fitbit filed for a $100?million initial public offering, but it now has to compete against a plethora of other fitness trackers on the market. The Apple Watch was been launched amidst a great deal of publicity, but it comes with no guarantees for Apple - a company that needs a lot of new revenues on a product to move the needle. Finally, the creation of the Oculus Rift virtual reality (VR) headsets could finally bring VR to the masses. The company has already been bought by Facebook for over $2?billion. Garmin, as a global positioning system (GPS), and Samsung Galaxy Gear, as a smart watch, are other popular wearables.

What is clear is that, based on the history of wearable technology, devices that move the masses are far and between. The successes that do make it, however, can change the world and generate chart-topping returns. Meanwhile, people's needs change over time, and include entertainment, activity, sport, and now most importantly health. This brings wearables such as Quell to the market. When strapped on the body Quell predicts and detects the onset of chronic pain and stimulates nerves to block pain signals to the brain. Other wearables to measure blood alcohol content, athletic performance, blood sugar, heart rate, and many other bioindicators rapidly came to the market as the desire for health monitoring grew. This may become more demanding as the interest in personal medicine grows.

1.2 Introduction to BSN Technology


Wearable technology including sensors, sensor networks, and the associated devices has opened its space in a variety of applications. Long-term, noninvasive, and nonintrusive monitoring of the human body through collecting as much biometric data and state indicators as possible is the major goal of healthcare wearable technology developers. Patients suffering from diabetes need a simple noninvasive tool to monitor their blood sugar on an hourly basis. Those suffering from seizure require the necessary instrumentation to alarm them before any seizure onset to prevent them from fall injury. The stroke patients need their heart rate recorded constantly. These are only a small number of examples which show how crucial and necessary wearable healthcare systems can be.

At the Wearable Technology Conference in 2018, the winners of seven wearable device producers were introduced. These winners include the best ones in Lifestyle with the objective of 'play stress away'; Sports and Fitness for making a football performance device, healthcare for developing a smart eyewear with assistive artificial intelligence capabilities for the blind and visually impaired; Industrial for designing a unique smart and connected industry 4.0 safety shoe; Smart Clothing Challenge for the nonintrusive acquisition of heart signals that will enable pervasive health monitoring, emotional state assessment, drowsiness detection, and identity recognition; Smart Lamp, which allows you to move the light in any direction without moving the lamp; and Connected Living Challenge, for creating accessories linking braintech with fashion design. Headpieces and earrings use electroencephalography (EEG) technology, capturing and providing users with brain data, allowing them to be conscious of their mental state in real time, for example for reducing anxiety and depression or increasing focus or relaxation of the user [1]. This simple example together with the above examples clearly show the diversity in applications of wearable technology. The aim of this book is therefore to familiarise readers with sensors, connections, signal processing tools and algorithms, electronics, communication systems, and networking protocols as well as many applications of wearable devices for the monitoring of mental, metabolic, physical, and physiological states of the human body.

Disease prevention, patient monitoring, and disable and elderly homecare have become the major objectives for investment in social health and public wellbeing. According to the World Health Organization (WHO), an ageing population is becoming a significant problem and degenerative brain diseases, such as dementia and depression, are increasingly seen in people while a bad lifestyle is causing millions of people to suffer from obesity or chronic diseases. It is thus reasonable to expect that this circumstance will only contribute to an ongoing decline in the quality of services (QoSs) provided by an already overloaded healthcare system [2]. A remote low-cost monitoring strategy, therefore, would significantly promote social and clinical wellbeing. This can only be achieved if sufficient reliably recorded information from the human body is available. Such information may be metabolic, biological, physiological, behavioural, psychological, functional, or motion-related.

On the other hand, the development of mobile telephone systems since the early 1990s and its improvement till now together with the availability of large size archiving and wideband communication channels significantly increase the chance of achieving the above objectives without hospitalising the caretakers in hospitals and care units for a long time. This may be considered a revolution in human welfare. More effective and efficient data collection from the human body has therefore a tremendous impact and influence on healthcare and the technology involved. The state of a patient during rest, walking, working, and sleeping can be well recognised if all the biomarkers of the physiological, biological, and behavioural changes of human body can be measured and processed. This requirement sparks the need for deployment of a multisensor and multimodal data collection system on the body. A body sensor network (BSN) therefore is central to a complete solution for patient monitoring and healthcare. Several key applications benefit from the advanced integration of BSNs, often called body area networks (BANs), with the new mobile communication technology [3, 4].

The main applications of BSNs are expected to appear in the healthcare domain, especially for the continuous monitoring and logging of vital parameters of elderly people or patients suffering from degenerative diseases such as dementia or chronic diseases such as diabetes, asthma, and heart attacks. As an example, a BAN network on a patient can alert the hospital, even before they have a heart attack, through measuring changes in their vital signs, or placing it on a diabetic patient could auto-inject insulin through a pump as soon as their insulin level declines.

The IEEE 802.15 Task Group 6 (BAN) is developing a communication standard optimised for reliable low-power devices and operation on, in, or around the human body (but not limited to humans) to serve a variety of applications including medical, consumer electronics/personal entertainment, and security [5]. This was approved on 22 July 2011 and the first meeting of IEEE 802.15 wireless personal area network (WPAN) was held on 3 March 2017.

The BSN technology benefits from developments in various areas of sensors, automation, communications, and more closely the vast advances in wired and wireless sensor networks (WSNs) for short- and long-range communications and industrial control. For...

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