Artificial neural networks to model and diagnose cardiovascular systems
- Pacific Northwest Lab., Richland, WA (United States); and others
In this paper, a novel approach to modeling and diagnosing the cardiovascular system is introduced. A model exhibits a subset of the dynamics of the cardiovascular behavior of an individual by using a recurrent artificial neural network. Potentially, a model will be incorporated into a cardiovascular diagnostic system. This approach is unique in that each cardiovascular model is developed from physiological measurements of an individual. Any differences between the modeled variables and. the actual variables of an individual at a given time are used for diagnosis. This approach also exploits sensor fusion to optimize the utilization of biomedical sensors. The advantage of sensor fusion has been demonstrated in applications including control and diagnostics of mechanical and chemical processes.
- DOE Contract Number:
- AC06-76RL01830
- OSTI ID:
- 269829
- Report Number(s):
- CONF-951050-; TRN: 96:002072-0002
- Resource Relation:
- Conference: Conference of the Institute of Electrical and Electronics Engineers, Inc., Portland, OR (United States), 10-12 Oct 1995; Other Information: PBD: 1995; Related Information: Is Part Of IEEE technical applications conference and workshops - Northcon/95; PB: 430 p.
- Country of Publication:
- United States
- Language:
- English
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