A team of researchers has developed a smartphone-based system to assess obstructive sleep apnea (OSA) severity while a patient is awake and analyse the sleep-wake activity.<\/p>\n
Currently, patients are diagnosed using polysomnography (PSG) to record brain waves, blood oxygen level, heart rate, breathing and eye and leg movements overnight.<\/p>\n
The new system, which does not require contact sensors, can be installed onto a smartphone or other device that utilises ambient microphones.<\/p>\n
It both analyses speech while the user is awake and records and evaluates overnight breathing sounds using new technology that is simpler to use and significantly less expensive than PSG, said the team from Ben-Gurion University of the Negev (BGU).<\/p>\n
\u201cWe\u2019ve developed technology that could help diagnose OSA and sleep disorders in a convenient way,\u201d said Dr Yaniv Zigel, head of BGU\u2019s biomedical signal processing research lab (BSP) in a statement.<\/p>\n
\u201cThe audio-analysis application can record speech signals from awake subjects. Now, we will be able to get a fast, OSA severity estimation without an overnight sleep study,\u201d added professor Ariel Tarasiuk, head of the sleep-wake disorders unit at Soroka University Medical Center in Beer-Sheva.<\/p>\n
Researchers tested the new speech and breathing sound analysis systems on more than 350 subjects, along with PSG, in laboratory and at-home settings.<\/p>\n
They were able to reliably evaluate sleep quality parameters such as sleep-wake activity, snoring severity and OSA using this system.<\/p>\n
\u201cWe are excited about this non-contact sleep tracking system which does not require patients to wear uncomfortable monitoring equipment on their body,\u201d Tarasiuk added.<\/p>\n
The application can also be very useful for CPAP (continuous positive airway pressure) machine users who want to check the effectiveness of their sleep apnea therapy.<\/p>\n
IANS<\/p>\n
Picture courtesy: Alamy Images<\/p>\n
Pictures has been used for illustrative purposes alone<\/p>\n
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