Use of neural networks for detection of artifacts in arterial pressure waveforms
- 13 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Two neural net architectures are applied to the problem of detecting artifacts in pulsatile pressure waveforms emanating from catheters in anesthetized patients awaiting cardiac surgery. A three-layer back-propagation network with 21 nodes in each layer satisfactorily detected all artifacts and falsely characterized none of the patterns. A competitive learning network, although easier to build and train, did not perform nearly so well. In both cases, the networks were trained on one set of data and tested on a different set. Both sets of data were taken from an anesthetized patient about to undergo cardiac surgery.Keywords
This publication has 3 references indexed in Scilit:
- Neurocomputing, Volume 1Published by MIT Press ,1988
- An efficient AI based algorithm for validating pulsatile arterial pressure waveformsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1988
- Parallel Distributed ProcessingPublished by MIT Press ,1986