Hypoxia severity impacts on cortical activity in moderate to severe OSA patients

Obstructive Sleep Apnea (OSA) is an important respiratory disease characterized by recurrent blockages of the throat (‘upper airway’) during sleep. These blockages result in short lapses in breathing. The low oxygen levels and disruption of sleep caused by OSA contribute to many problems including: sleepiness, poor quality of life, awakenings during sleep, hypertension, heart disease, strokes, and dementia. OSA is usually diagnosed by a ‘sleep study’: patients stay overnight in the hospital and many biologic signals (i.e., brain wave patterns, heart rate, oxygen levels, breathing effort) are collected over 8 or more hours. The severity of OSA is usually measured by the apnea-hypopnea index (AHI), which is the number of times the throat closes or narrows per hour of sleep. However, the AHI does not predict symptoms of health outcomes of sleep apnea well. We believe that new ways of looking at the information collected during sleep studies might help predict what problems someone with OSA will have. The purpose of this project is to apply advanced computer techniques to information collected from a large group of patients with sleep apnea in order to develop tools that can better predict brain function in patients with sleep apnea.

Faculty Supervisor:

Najib Ayas

Student:

Partner:

Legacy for Airway Health

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

The University of British Columbia

Program: