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Proceedings Paper

Real-world applications of artificial neural networks to cardiac monitoring using radar and recent theoretical developments
Author(s): Mary Lou Padgett; John L. Johnson; V. Rao Vemuri
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Paper Abstract

This paper focuses on use of a new image filtering technique, Pulsed Coupled Neural Network factoring to enhance both the analysis and visual interpretation of noisy sinusoidal time signals, such as those produced by LLNL's Microwave Impulse Radar motion sensor. Separation of a slower, carrier wave from faster, finer detailed signals and from scattered noise is illustrated. The resulting images clearly illustrate the changes over time of simulated heart motion patterns. Such images can potentially assist a field medic in interpretation of the extent of combat injuries. These images can also be transmitted or stored and retrieved for later analysis.

Paper Details

Date Published: 4 April 1997
PDF: 11 pages
Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); doi: 10.1117/12.271483
Show Author Affiliations
Mary Lou Padgett, Padgett Computer Innovations, Inc. (United States)
John L. Johnson, U.S. Army Missile Command (United States)
V. Rao Vemuri, Univ. of California/Davis and Lawrence Livermore National Lab. (United States)


Published in SPIE Proceedings Vol. 3077:
Applications and Science of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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