A biosystems approach to industrial patient monitoring and diagnostic devices [electronic resource] / Gail Baura.

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 those medical devices that are computer based, and are therefore referred to as medical instruments. Further, the med...

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Bibliographic Details
Online Access: Full Text (via Morgan & Claypool)
Main Author: Baura, Gail D.
Other title:Synthesis digital library of engineering and computer science.
Format: Electronic eBook
Language:English
Published: San Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, ©2008.
Edition:1st ed.
Series:Synthesis lectures on biomedical engineering (Online) ; # 12.
Subjects:

MARC

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245 1 2 |a A biosystems approach to industrial patient monitoring and diagnostic devices  |h [electronic resource] /  |c Gail Baura. 
250 |a 1st ed. 
260 |a San Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA) :  |b Morgan & Claypool Publishers,  |c ©2008. 
300 |a 1 electronic text (xi, 93 pages : color illustrations) :  |b digital file. 
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504 |a Includes bibliographic references. 
505 0 |a Medical devices -- Medical device industry -- Medical instrumentation -- Patient monitoring devices -- Diagnostic devices -- System theory -- System theory for physiologic signals -- Filters -- Modeling -- Patient monitoring devices -- Masimo pulse oximetry -- Interflo medical continuous thermodilution -- Cardio dynamics impedance cardiography -- Aspect medical depth of anesthesia monitoring -- Diagnostic devices -- Neopath cervical cancer screening. 
520 |a 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 those medical 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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650 0 |a System theory.  |0 http://id.loc.gov/authorities/subjects/sh85131743. 
650 0 |a Medical instruments and apparatus industry  |z United States.  |0 http://id.loc.gov/authorities/subjects/sh2008107421. 
650 0 |a Patient monitoring  |x Equipment and supplies.  |0 http://id.loc.gov/authorities/subjects/sh85098705. 
690 |a System theory. 
690 |a Machine intelligence. 
690 |a Patient monitoring. 
690 |a In vitro diagnostics. 
690 |a Pseudorandom binary sequence. 
690 |a Adaptive filtering. 
690 |a Wavelet transforms. 
690 |a ARMAX model. 
690 |a Artificial neural networks. 
690 |a Fuzzy model. 
690 |a Fuzzy control. 
730 0 |a Synthesis digital library of engineering and computer science.  |0 http://id.loc.gov/authorities/names/n2016188085. 
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