Boston, MA — March 27, 2024 — Beacon Biosignals announced today that it has received FDA 510(k) clearance for SleepStageML™️, an advanced machine learning software that automatically stages sleep from electroencephalogram (EEG) signals of clinical polysomnography (PSG) recordings to aid in the diagnosis and evaluation of sleep and sleep-related disorders. Beacon Biosignals is a health technology company focused on accelerating the development of therapies for neurological, psychiatric, and sleep disorders, and SleepStageML opens the door for more consistent, efficient, and precise sleep staging for these therapeutic areas. This latest clearance complements Beacon's previous FDA clearance of the Dreem 3S wearable headband and integrated algorithms, providing a comprehensive solution for precisely measuring sleep architecture across home and clinical settings.
"With FDA clearances for both SleepStageML and Dreem 3S™ headband, Beacon now provides an unparalleled capability to measure sleep physiology whether studies are conducted in-home or in-clinic," said Jacob Donoghue, MD, PhD, CEO of Beacon Biosignals. "Beacon's powerful analytics platform allows for rich analysis of clinical datasets across multiple environments to spur innovation in therapies for sleep disorders as well as neurological and psychiatric conditions with sleep comorbidities."
SleepStageML leverages an advanced deep-learning model to robustly score sleep stages. The model was trained on a massive dataset containing hundreds of thousands of hours of PSG recordings from both healthy individuals and patients with a diverse set of sleep disorders, neurologic disease, and psychiatric disease, acquired across numerous clinical sites. Clinical validation testing demonstrated that SleepStageML performs as well or better than individual human experts as reported in literature (Guillot et al, 2020; Rosenberg et al, 2013).
Key benefits of SleepStageML include:
- Automating the labor-intensive manual sleep staging process
- Reducing subjective variability in scoring between human experts
- Supporting faster PSG analysis turnaround time
"The advanced machine learning algorithms powering SleepStageML reduce human scoring variability and increase precision of sleep measurements," added Brandon Westover, MD, PhD, Landau Professor of Neurology at Harvard Medical School and co-founder of Beacon Biosignals. "This automated approach unlocks new clinical insights to drive forward therapy development for sleep and sleep-related disorders."
SleepStageML is also the first medical device within the sleep space to be FDA cleared with a Predetermined Change Control Plan (PCCP), allowing Beacon to continuously improve the sleep staging machine learning algorithm while still operating under the initial 510(k) clearance. The Predetermined Change Control Plan outlines strict validation testing that must be passed for any updates to the AI/ML model, ensuring improved performance compared to the originally cleared version. This allows Beacon to iteratively refine SleepStageML's algorithms over time while verifying through comprehensive testing that the updated software meets safety and efficacy standards.
"SleepStageML's approved PCCP is a game changing development for the sleep field," said Alexander Chan, PhD, VP of Analytics and Machine Learning at Beacon Biosignals. "With this regulatory pathway, we can provide even more accurate and robust sleep staging capabilities over time. This ability to iteratively enhance SleepStageML will be invaluable for generating insights to accelerate sleep therapy research and development."
This FDA clearance represents a major milestone that bolsters Beacon Biosignals' powerful machine learning platform for rapidly analyzing large neurophysiology datasets. Beacon's array of analytical solutions positions the company as a premier technology partner for pharmaceutical companies, research institutions, and clinical trial organizations seeking to incorporate high-fidelity brain monitoring and sleep measurement into their neuroscience, psychiatry, sleep, and neurodegenerative disease research programs. Interested partners can inquire about collaborating with Beacon by visiting https://beacon.bio/contact.
About Beacon Biosignals
Beacon's machine learning platform for EEG enables and accelerates new treatments that transform the lives of patients with neurological, psychiatric or sleep disorders. Through novel machine learning algorithms, EEG wearables, large Clinico-EEG RWE datasets, and advances in cloud-based scientific computing, Beacon Biosignals is changing the way patients are treated for disorders of the brain. For more information, visit https://beacon.bio/. To work together, visit https://beacon.bio/contact. Follow us on Twitter (@Biosignals) or LinkedIn (https://www.linkedin.com/company/beacon-biosignals).
For media inquiries, please contact info@beacon.bio.
Sources
- FDA 510(k) Clearance Details
- Guillot A, Sauvet F, During EH, Thorey V. Dreem Open Datasets: Multi-Scored Sleep Datasets to Compare Human and Automated Sleep Staging. IEEE T Neur Sys Reh 2020;28(9):1955–65.
- Rosenberg RS, Hout SV. The American Academy of Sleep Medicine Inter-scorer Reliability Program: Sleep Stage Scoring. J Clin Sleep Med 2013;09(01):81–7.