Biomaterial Database

Considerations for developing a clinical capnogram monitoring system. 1997

J M Goldman

University of Colorado Health Sciences Center, Denver 80262, USA.

Clinical monitoring and diagnostic systems may require the analysis of multiple physiologic signals to generate a diagnosis. The complexity of these systems is formidable for at least two reasons: clinical physiologic signals are noisy, and systems built around multiple signals may fail when any single signal is absent. In view of these limitations, we have been developing a clinical respiratory CO2 waveform (capnogram) diagnostic system. The purpose of this system is to develop a differential diagnosis from a single signal for subsequent evaluation within the context of multiple single-signals. This paper will review the development issues which we have been confronting, and discuss the tools and methods which have been successful.

UI	MeSH Term	Description	Entries
D008991	Monitoring, Physiologic	The continuous measurement of physiological processes, blood pressure, heart rate, renal output, reflexes, respiration, etc., in a patient or experimental animal; includes pharmacologic monitoring, the measurement of administered drugs or their metabolites in the blood, tissues, or urine.	Patient Monitoring,Monitoring, Physiological,Physiologic Monitoring,Monitoring, Patient,Physiological Monitoring
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328	Adult	A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available.	Adults
D012815	Signal Processing, Computer-Assisted	Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity.	Digital Signal Processing,Signal Interpretation, Computer-Assisted,Signal Processing, Digital,Computer-Assisted Signal Interpretation,Computer-Assisted Signal Interpretations,Computer-Assisted Signal Processing,Interpretation, Computer-Assisted Signal,Interpretations, Computer-Assisted Signal,Signal Interpretation, Computer Assisted,Signal Interpretations, Computer-Assisted,Signal Processing, Computer Assisted
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D019296	Capnography	Continuous recording of the carbon dioxide content of expired air.	Capnographies

Related Publications

J M Goldman

A scoring system for capnogram biofeedback: preliminary findings.

June 1998, Applied psychophysiology and biofeedback,

J M Goldman

Considerations for integration of a physiological radar monitoring system with gold standard clinical sleep monitoring systems.

January 2013, Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference,

J M Goldman

Developing a patient care monitoring system.

February 2000, Canadian journal of psychiatry. Revue canadienne de psychiatrie,

J M Goldman

Developing a therapeutic relationship monitoring system for group treatment.

June 2018, Psychotherapy (Chicago, Ill.),

J M Goldman

Considerations in designing a system for developing dental caries models.

November 1969, Currents in modern biology,

J M Goldman

Considerations for the design of a Web-based clinical monitoring and educational system for elderly patients.

January 2001, Journal of the American Medical Informatics Association : JAMIA,