Sleep apnea, a common but often undiagnosed condition affecting millions worldwide, disrupts sleep and can exacerbate various health issues. The National Council on Aging reports that approximately 39 million adults in the U.S. and 936 million globally suffer from obstructive sleep apnea (OSA), a condition where relaxed airways obstruct breathing during sleep, causing oxygen supply disruptions up to 30 times per hour. This leads to poor sleep quality and daytime fatigue, with long-term effects including heightened risks of cardiovascular, neurodegenerative, and metabolic diseases. Mount Sinai Health System’s recent funding announcement highlights the urgent need for improved diagnosis and treatment.
The challenges in diagnosing sleep apnea, coupled with research showing that positive airway pressure treatment can reduce healthcare costs, are driving healthcare organizations and agencies like the U.S. Food and Drug Administration to explore innovative solutions. Health tech advancements leveraging algorithms, machine learning, and wearable sensors are showing promise. For instance, the jaw-sensing sleep apnea device from Belgian startup Sunrise, which recently received approval, analyzes bio-signals from mandibular movements to calculate respiratory patterns, potentially widening access to sleep apnea care.
EnsoData’s device-agnostic deep learning and a new feature on the Samsung Galaxy Watch are among the innovations poised to improve sleep apnea diagnosis and treatment. EnsoData’s FDA-cleared AI algorithm, EnsoSleep, utilizes data from any FDA-cleared pulse oximeter to aid in diagnosing sleep disorders. “Expanding EnsoData’s capability to collect and analyze signals from simple, wearable pulse ox devices will accelerate the identification, diagnosis, and treatment of sleep-disordered breathing events, including sleep apnea,” said Justin Mortara, president and CEO of EnsoData.
Samsung’s Galaxy Watch, set to release its FDA-approved sleep apnea feature in the U.S. in the third quarter, will provide users with insights into their sleep health habits. The watch’s bioactive sensor tracks blood oxygen levels during sleep, helping to detect moderate to severe OSA.
Mount Sinai is also at the forefront of research, developing machine learning models to predict the consequences of serious sleep disorders. The AI model under development aims to provide a more accurate risk profile for sleep apnea patients by analyzing multiple sleep metrics. This approach could revolutionize the clinical management of OSA, offering a more nuanced understanding of the condition’s severity.
Despite these advancements, challenges remain. PAP machines, a common treatment for sleep apnea, require an adjustment period for users, and there have been concerns about the safety of certain devices. The FDA reported 561 deaths connected to a recall of Philips Respironics devices in 2021 due to issues with polyester-based polyurethane foam.
To conclude, the fight against sleep apnea is advancing on multiple fronts, from innovative diagnostic tools to AI-driven predictive models. These developments hold the promise of transforming sleep apnea care, improving patient outcomes, and reducing the burden on healthcare systems.
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