|
Showing 1 - 6 of
6 matches in All Departments
Healthcare sensor networks (HSNs) now offer the possibility to
continuously monitor human activity and physiological signals in a
mobile environment. Such sensor networks may be able to reduce the
strain on the present healthcare workforce by providing new
autonomous monitoring services ranging from simple user-reminder
systems to more advanced monitoring agents for preventive,
diagnostic, and rehabilitative purposes. Potential services include
reminding people to take their medication, providing early warning
for the onset of heart attacks or epileptic seizures, and
monitoring a child's physical activity in order to assess their
growth and mental development. Healthcare Sensor Networks:
Challenges Toward Practical Implementation discusses the
fundamental concepts in designing and building such networks. It
presents the latest developments in HSNs, explores applications of
the technology, and provides insights into practical design and
deployment challenges. Bringing together contributions from
international experts in the field, the book highlights the key
areas that require further research for HSNs to become a
technological and commercially viable reality. The first part of
the book concentrates on the engineering challenges, covering new
biosensors, energy harvesting techniques, new wireless
communication methods, and novel security approaches. Building from
single sensing devices to networked sensing systems, the second
part of the book looks at various health applications of HSNs. It
addresses the human-centric requirements that should be considered
in the design of HSN technologies-cost, portability, functionality,
and user acceptance-and demonstrates how engineering compromises
must be made in HSN solutions. A useful and timely resource for
researchers, postgraduate students, and engineers looking for
innovative solutions in healthcare, this book will also be of
interest to medical and allied he
As in many other fields, biomedical engineers benefit from the use
of computational intelligence (CI) tools to solve complex and
non-linear problems. The benefits could be even greater if there
were scientific literature that specifically focused on the
biomedical applications of computational intelligence techniques.
The first comprehensive field-specific reference, Computational
Intelligence in Biomedical Engineering provides a unique look at
how techniques in CI can offer solutions in modelling, relationship
pattern recognition, clustering, and other problems particular to
the field. The authors begin with an overview of signal processing
and machine learning approaches and continue on to introduce
specific applications, which illustrate CI's importance in medical
diagnosis and healthcare. They provide an extensive review of
signal processing techniques commonly employed in the analysis of
biomedical signals and in the improvement of signal to noise ratio.
The text covers recent CI techniques for post processing ECG
signals in the diagnosis of cardiovascular disease and as well as
various studies with a particular focus on CI's potential as a tool
for gait diagnostics. In addition to its detailed accounts of the
most recent research, Computational Intelligence in Biomedical
Engineering provides useful applications and information on the
benefits of applying computation intelligence techniques to improve
medical diagnostics.
As in many other fields, biomedical engineers benefit from the use
of computational intelligence (CI) tools to solve complex and
non-linear problems. The benefits could be even greater if there
were scientific literature that specifically focused on the
biomedical applications of computational intelligence techniques.
The first comprehensive field-specific reference, Computational
Intelligence in Biomedical Engineering provides a unique look at
how techniques in CI can offer solutions in modelling, relationship
pattern recognition, clustering, and other problems particular to
the field. The authors begin with an overview of signal processing
and machine learning approaches and continue on to introduce
specific applications, which illustrate CI's importance in medical
diagnosis and healthcare. They provide an extensive review of
signal processing techniques commonly employed in the analysis of
biomedical signals and in the improvement of signal to noise ratio.
The text covers recent CI techniques for post processing ECG
signals in the diagnosis of cardiovascular disease and as well as
various studies with a particular focus on CI's potential as a tool
for gait diagnostics. In addition to its detailed accounts of the
most recent research, Computational Intelligence in Biomedical
Engineering provides useful applications and information on the
benefits of applying computation intelligence techniques to improve
medical diagnostics.
Healthcare sensor networks (HSNs) now offer the possibility to
continuously monitor human activity and physiological signals in a
mobile environment. Such sensor networks may be able to reduce the
strain on the present healthcare workforce by providing new
autonomous monitoring services ranging from simple user-reminder
systems to more advanced monitoring agents for preventive,
diagnostic, and rehabilitative purposes. Potential services include
reminding people to take their medication, providing early warning
for the onset of heart attacks or epileptic seizures, and
monitoring a child's physical activity in order to assess their
growth and mental development. Healthcare Sensor Networks:
Challenges Toward Practical Implementation discusses the
fundamental concepts in designing and building such networks. It
presents the latest developments in HSNs, explores applications of
the technology, and provides insights into practical design and
deployment challenges. Bringing together contributions from
international experts in the field, the book highlights the key
areas that require further research for HSNs to become a
technological and commercially viable reality. The first part of
the book concentrates on the engineering challenges, covering new
biosensors, energy harvesting techniques, new wireless
communication methods, and novel security approaches. Building from
single sensing devices to networked sensing systems, the second
part of the book looks at various health applications of HSNs. It
addresses the human-centric requirements that should be considered
in the design of HSN technologies-cost, portability, functionality,
and user acceptance-and demonstrates how engineering compromises
must be made in HSN solutions. A useful and timely resource for
researchers, postgraduate students, and engineers looking for
innovative solutions in healthcare, this book will also be of
interest to medical and allied he
Healthcare costs around the globe are on the rise, creating a
strong need for new ways of assisting the requirements of the
healthcare system. Besides applications in other areas, neural
networks have naturally found many promising applications in the
health and medicine areas. ""Neural Networks in Healthcare:
Potential and Challenges"" presents interesting and innovative
developments from leading experts and scientists working in health,
biomedicine, biomedical engineering, and computing areas. This book
covers many important and state-of-the-art applications in the
areas of medicine and healthcare, including: cardiology,
electromyography, electroencephalography, gait and human movement,
therapeutic drug monitoring for patient care, sleep apnea, and
computational fluid dynamics areas. ""Neural Networks in
Healthcare: Potential and Challenges"" is a useful source of
information for researchers, professionals, lecturers, and students
from a wide range of disciplines. Readers of this book will be able
to use the ideas for further research efforts in this very
important and highly multidisciplinary area.
Recent years have seen many new developments in computational
intelligence (CI) techniques and, consequently, this has led to an
exponential increase in the number of applications in a variety of
areas, including: engineering, finance, social and biomedical. In
particular, CI techniques are increasingly being used in biomedical
and human movement areas because of the complexity of the
biological systems, as well as the limitations of the existing
quantitative techniques in modelling. ""Computational Intelligence
for Movement Sciences: Neural Networks and Other Emerging
Techniques"" contains information regarding state-of-the-art
research outcomes and cutting-edge technology from leading
scientists and researchers working on various aspects of the human
movement. Readers of this book will gain an insight into this
field, as well as access to pertinent information, which they will
be able to use for continuing research in this area.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
|