@article{ETD,
      school = {Ph.D.},
      author = {Snider, Brian R.},
      url = {http://digitalcollections.ohsu.edu/record/8573},
      title = {Sleep signal processing for disordered breathing event  detection and severity estimation},
      publisher = {Oregon Health and Science University},
      abstract = {Sleep-disordered breathing (SDB) is recognized as a  widespread, under-diagnosed condition associated with many  detrimental health problems. The condition places a  significant burden on the individual and the healthcare  system alike, with untreated SDB patients utilizing  national health resources at twice the usual rate. The most  common form of SDB is obstructive sleep apnea,  characterized by frequent transient reductions of oxygen  saturation, cessations of ventilatory airflow, and collapse  or obstruction of the upper airway. Other forms of SDB  include hypopnea, characterized by a reduction of  ventilatory airflow; central apnea, with a cessation of  ventilatory effort and airflow; and mixed apnea, a  combination of central and obstructive apnea.},
      number = {ETD},
      doi = {https://doi.org/10.6083/h702q723n},
      recid = {8573},
      address = {2020},
}