Automatic Classification of Spirometric Data

@article{Tsai1979AutomaticCO,
  title={Automatic Classification of Spirometric Data},
  author={M. J. Tsai and Russell L. Pimmel and James F. Donohue},
  journal={IEEE Transactions on Biomedical Engineering},
  year={1979},
  volume={BME-26},
  pages={293-298}
}
Pattern recognition principles have been applied to 200 sets of spirometric data obtained from pulmonary function laboratory patients. Each patient was classified by a pulmonary specialist as normal, restricted, or mildly, moderately, severely, or very severely obstructed. Each patient was represented by a five-element pattern vector consisting of forced… CONTINUE READING