22 March 1999 Applications of neural networks to the radarcardiogram (RCG)
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Displacement cardiography techniques such as the ballistocardiogram and seismocardiogram use accelerometers to measure body motion caused by the beating heart. The radarcardiogram (RCG) measures this motion using highly sensitive radar developed at the Georgia Tech Research Institute. Combining the portability and non-invasiveness of radar along with neural network processing techniques opens a host of potential new applications including unknown person identification, stress measurement, and medical diagnosis. Correlation between displacement cardiography and the RCG will be discussed along with preliminary research using RCG data and a neural network to identify unknown persons. It was found that a neural network could accurately identify the RCG of an unknown individual out of a small pool of training data. In addition, the system was able to correctly reject individuals not within the training set.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jonathan L. Geisheimer, Eugene F. Greneker, "Applications of neural networks to the radarcardiogram (RCG)", Proc. SPIE 3722, Applications and Science of Computational Intelligence II, (22 March 1999); doi: 10.1117/12.342891; https://doi.org/10.1117/12.342891

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