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A Biosystems Approach to Industrial Patient Monitoring and Diagnostic Devices (Synthesis Lectures on Emerging Engineering Technologies) - Softcover
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Inhaltsangabe
A medical device is an apparatus that uses engineering and scientific principles to interface to physiology and diagnose or treat a disease. In this Lecture, we specifically consider thosemedical devices that are computer based, and are therefore referred to as medical instruments. Further, the medical instruments we discuss are those that incorporate system theory into their designs. We divide these types of instruments into those that provide continuous observation and those that provide a single snapshot of health information. These instruments are termed patient monitoring devices and diagnostic devices, respectively.Within this Lecture, we highlight some of the common system theory techniques that are part of the toolkit of medical device engineers in industry. These techniques include the pseudorandom binary sequence, adaptive filtering, wavelet transforms, the autoregressive moving average model with exogenous input, artificial neural networks, fuzzy models, and fuzzy control. Because the clinical usage requirements for patient monitoring and diagnostic devices are so high, system theory is the preferred substitute for heuristic, empirical processing during noise artifact minimization and classification.
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Reseña del editor
A medical device is an apparatus that uses engineering and scientific principles to interface to physiology and diagnose or treat a disease. In this Lecture, we specifically consider thosemedical devices that are computer based, and are therefore referred to as medical instruments. Further, the medical instruments we discuss are those that incorporate system theory into their designs. We divide these types of instruments into those that provide continuous observation and those that provide a single snapshot of health information. These instruments are termed patient monitoring devices and diagnostic devices, respectively.Within this Lecture, we highlight some of the common system theory techniques that are part of the toolkit of medical device engineers in industry. These techniques include the pseudorandom binary sequence, adaptive filtering, wavelet transforms, the autoregressive moving average model with exogenous input, artificial neural networks, fuzzy models, and fuzzy control. Because the clinical usage requirements for patient monitoring and diagnostic devices are so high, system theory is the preferred substitute for heuristic, empirical processing during noise artifact minimization and classification.
Biografía del autor
Gail Dawn Baura received a BSEE from Loyola MarymountUniversity in 1984, and an MSEE and MSBME from Drexel University in 1987. She received a PhD in Bioengineering from the University of Washington in 1993. Between these graduate degrees, Dr. Baura worked as a loop transmission systems engineer at AT&T Bell Laboratories. Since graduation, she has served in a variety of research and development positions at IVAC Corporation, Cardiotronics Systems, Alaris Medical Systems, and VitalWave Corporation (now Tensys Medical). Her most recent industrial position was Vice President of Research and Chief Scientist at CardioDynamics. In 2006, she returned to academia as a Professor at Keck Graduate Institute of Applied Life Sciences in Claremont, CA. Dr. Baura's textbook, System Theory and Practical Application of Biomedical Signals (Wiley-IEEE Press, 2002), is part of the IEEE Series in Biomedical Engineering. Her textbook, Engineering Ethics: An Industrial Perspective (Academic Press, 2006), was written to provide industrial material for engineering programs wishing to fulfill the accreditation ethics requirement. Dr. Baura is a senior member of IEEE, associate editor of IEEE Engineering in Medicine and Biology Magazine, and a biomedical engineering evaluator for the Accreditation Board of Engineering Technology. She holds 15 issued and 6 pending U.S. patents. Her research interests are the application of system theory to patient monitoring and other devices.
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