Samsung has announced that its Galaxy Ring has secured US Food and Drug Administration (FDA) approval for an advanced sleep apnea detection feature. The newly authorized tool aims to help users identify potential causes of persistent fatigue despite full nights of rest.
Advanced Detection Features
The company initially obtained De Novo FDA authorization for sleep apnea detection across its Galaxy Watch and Galaxy Ring hardware in February 2024. That preliminary clearance was strictly limited to identifying symptoms associated with moderate to severe forms of the condition.
The updated software builds upon those capabilities by incorporating artificial intelligence to measure the exact frequency of breathing interruptions per hour of sleep. By utilizing the Samsung Health Monitor app following at least five hours of sleep across two nights within a ten-day window, users can receive classifications indicating mild, occasional, or frequent sleep apnea.
Samsung emphasizes that the device does not replace professional medical evaluations and that only a physician can officially diagnose sleep apnea. Instead, the company notes that the technology can facilitate productive conversations with healthcare professionals.
Competitive Landscape and Availability
Rival smart ring manufacturers Oura and Superhuman currently lack FDA approval for sleep apnea detection, though both alternatives feature nighttime disturbance tracking capable of highlighting potential signs of the disorder. Meanwhile, Samsung and Oura remain embroiled in an intellectual property dispute regarding smart ring patents, with an initial ruling anticipated shortly.
In addition to the Galaxy Ring, this advanced sleep apnea detection capability is rolling out to the Galaxy Watch 9 operating on Wear OS 7.0 or newer software. Subsequent software updates will also extend the functionality to the Galaxy Watch 7 and Galaxy Watch 8 models.
Users seeking additional sleep assistance will find that Samsung has recently redesigned its Sleep Coaching tool to function effectively with reduced data inputs compared to previous iterations.
