Instead of spending the night in sleep labs or attaching to uncomfortable sensors while in their beds at home, people can use a smartphone to listen to their breathing and assess obstructive sleep apnea (OSA).
Ben-Gurion University of the Negev and Soroka University Medical Center researchers in Beersheba have developed a system to measure the severity of OSA and analyze sleepwake activity while a patient is awake, using a smartphone.
The application can also check a patient for the effectiveness of using a continuous positive airway pressure, or CPAP, machine for sleep apnea.
Dr. Yaniv Zigel, head of BGU’s biomedical signal processing research lab, said this technology is simpler and significantly less expensive to use than the current gold standard – overnight polysomnography.
The new system does not require any sensors to be connected to the patient; instead, it uses a program that can even be downloaded onto a smartphone to analyze speech and sleep sounds.
“One of the main goals of sleep medicine today is to improve early diagnosis and treatment of the flood of subjects presenting with sleep disorders,” said Prof. Ariel Tarasiuk, head of Soroka’s sleepwake disorders unit.
By using smartphone technology, it is possible to estimate the number of apnea and hypopnea (suspended or reduced breathing) events for each hour of sleep, even in people who are awake. The technology enables fast and accurate diagnosis of OSA without the need for an overnight sleep study, Zigel and Tarasiuk said.
Currently, all sleep studies require the subjects to be connected to numerous electrodes and sensors, with the data processed and visually examined, or mathematically transformed manually, to assess problems.
“This procedure is time-consuming, tedious and costly due to its complexity and the need for technical expertise; the market is begging for a better solution,” added Eliran Dafna, who developed the breathing-sound system as part of his doctoral research.
The new speech and breathing- sound analysis systems were tested on more than 350 subjects, using ambient microphones (or a smartphone) in parallel to conventional sleep studies in both lab and at-home settings.
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