@inproceedings{153a3dc08bdb4252a912c93e98533c6e,
title = "Blood pressure estimation using neural networks",
abstract = "Oscillometry is an indirect method to determine blood pressure. An inflatable and deflatable cuff is placed on arm to observe oscillations at different pressure levels. Thus, an envelope obtained from the oscillations is related to the blood pressure. In our work, we extract few features from the oscillometric waveforms, and estimate blood pressure using feedforward neural networks. Feature strength is evaluated by computing the standard deviation of the errors. The results are compared with the traditional maximum amplitude pressure algorithm. A large non-invasively collected database is used for this purpose.",
keywords = "Blood pressure estimation, Neural networks, Oscillometry",
author = "S. Colak and C. Isik",
year = "2004",
language = "English (US)",
isbn = "0780383419",
series = "2004 IEEE International Conference on Computational Intelligence for Measurements Systems and Applications, CIMSA",
pages = "21--25",
booktitle = "2004 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA",
note = "2004 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA ; Conference date: 14-07-2004 Through 16-07-2004",
}