000			04376nam a2200697 i 4500
001			6812514
003			IEEE
005			20200413152850.0
006			m eo d
007			cr cn |||m|||a
008			080128s2008 caua ob 000 0 eng d
020			_a1598292951 (electronic bk.)
020			_a9781598292954 (electronic bk.)
020			_a1598292943 (pbk.)
020			_a9781598292947 (pbk.)
024	7		_a10.2200/S00101ED1V01Y200702BME012 _2doi
035			_a(CaBNVSL)gtp00531398
035			_a(OCoLC)191562131
040			_aWAU _cWAU _dCaBNVSL
050		4	_aR856 _b.B383 2008
082	0	4	_a681/.761 _222
100	1		_aBaura, Gail D.
245	1	2	_aA biosystems approach to industrial patient monitoring and diagnostic devices _h[electronic resource] / _cGail Baura.
250			_a1st ed.
260			_aSan Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA) : _bMorgan & Claypool Publishers, _cc2008.
300			_a1 electronic text (xi, 93 p. : col. ill.) : _bdigital file.
490	1		_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v#12
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat Reader.
500			_aPart of: Synthesis digital library of engineering and computer science.
500			_aSeries from website.
504			_aIncludes bibliographic references.
505	0		_aMedical 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.
506	1		_aAbstract freely available; full-text restricted to subscribers or individual document purchasers.
510	0		_aCompendex
510	0		_aINSPEC
510	0		_aGoogle scholar
510	0		_aGoogle book search
520			_aA 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.
530			_aAlso available in print.
588			_aTitle from PDF t.p. (viewed on Nov. 5, 2008).
650		0	_aMedical instruments and apparatus _xDesign and construction.
650		0	_aMedical electronics _xEquipment and supplies.
650		0	_aSystem theory.
650		0	_aMedical instruments and apparatus industry _zUnited States.
650		0	_aPatient monitoring _xEquipment and supplies.
690			_aSystem theory.
690			_aMachine intelligence.
690			_aPatient monitoring.
690			_aIn vitro diagnostics.
690			_aPseudorandom binary sequence.
690			_aAdaptive filtering.
690			_aWavelet transforms.
690			_aARMAX model.
690			_aArtificial neural networks.
690			_aFuzzy model.
690			_aFuzzy control.
730	0		_aSynthesis digital library of engineering and computer science.
830		0	_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v#12.
856	4	2	_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6812514
999			_c561606 _d561606