With PSG, the patient must spend a whole night at a sleep center attached to electrodes that are in turn connected to an electroencephalograph, electrocardiograph, electrooculograph (for eye movements) and electromyograph (for muscle movements). The resulting data must be examined and manipulated mathematically to draw conclusions about sleep and wakefulness physiology. "This procedure is time-consuming, tedious and costly due to complexity and the need for technical expertise. The market is begging for a better solution," said researcher Eliran Dafna.
"We've developed a non-contact breathing sound algorithm that allows for a reliable estimation of whole-night sleep evaluation for detection of sleep quality, snoring severity and obstructive sleep apnea. It has the potential to reduce the cost and management effort of sleep disorders compared to PSG, the current standard of treatment, and could be used at home," said lead researcher Dr. Yaniv Zigel.
With the new BSA method, microphones only are used. Acoustic phenomena that define different breathing patterns, and also allow for them to be quantified, were identified by the researchers. These in turn allowed them to detect sleeping and wakefulness periods. Conclusions about the quality of sleep could then be made, based on the sleep vs. wakefulness patterns.
In a study, 80 volunteers were monitored by BSA while a control group of 70 others were monitored by the more complex PSG method. Given 150,000 individual sleep segments from all participants, BSA had an accuracy rate of 83.3%, compared with PSG.
"The results showed that sleep/wake activity and sleep quality parameters can be estimated solely by using breath sound analysis. This study highlights the potential of this innovative approach to measure sleep in research and clinical circumstances," said researcher Ariel Tarasiuk.