Diagnosing sleep apnea

A computer scientist from the University of Houston and a doctor at the University of Texas Health Science Center at Houston have teamed up to create a new, less invasive method of diagnosing sleep apnea.


A computer scientist from the University of Houston and a doctor at the University of Texas Health Science Center (UTHSC) at Houston have teamed up to create a new, less invasive method of diagnosing sleep apnea.


Sleep apnea is a serious disorder that causes a person to momentarily stop breathing while they sleep.


These pauses in breathing can occur many times an hour and can cause low oxygen levels in the blood and chronic sleepiness.


Approximately 24 per cent of men and nine per cent of women experience sleep apnea, but getting a diagnosis involves a procedure called polysomnography, also known as a sleep study.


But one of the difficulties in obtaining a sleep-apnea diagnosis is the invasive nature of current testing methods.


During a sleep study a subject has an average of more than 20 sensors attached to his or her head and body.


Jayasimha N Murthy, assistant professor of medicine from the Division of Pulmonary Critical Care Sleep Medicine at UTHSC at Houston, said: ‘It’s a very complex procedure where many physiological parameters are simultaneously monitored to help in the diagnosis of sleep disorders.


‘However, these sensors can disturb sleep and contribute to the patient’s anxiety.’


The new diagnostic procedure, developed by Ioannis Pavlidis, Eckhard-Pfeiffer Professor of Computer Science at the University of Houston, and Murthy, uses a thermal infrared camera to monitor breathing and airflow as a patient breathes in and out of their nose.


The measurements are then processed and produce results that have proved to be as accurate as traditional polysomnography.


The new method also provides doctors with more information about the patient’s breathing.


‘In contrast to the traditional one-dimensional methods, this new method is an imaging one and thus multi-dimensional,’ said Pavlidis.


‘We now can see how airflow is distributed locally throughout the extent of the nostril.


‘We get not a single, but multiple values for each nostril at every point in time.’


The researchers believe that this new technology could change the way sleep apnea is diagnosed, potentially helping millions sleep better and possibly live longer.