SleepStageML

by Beacon Biosignals  · Based in United States → — Building the future of brain health with AI-driven neurotechnology.
Neurology Pulmonology Sleep Medicine
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Regulatory Status Disclosed

Overview

SleepStageML by Beacon Biosignals is an advanced, FDA-cleared machine learning software designed to automate the staging of sleep from electroencephalogram (EEG) signals of clinical polysomnography (PSG) recordings. It is intended to assist qualified clinicians in the diagnostic evaluation and assessment of sleep quality in adult patients (aged 18 and older) within a clinical environment.

This software-only medical device leverages deep-learning models trained on extensive datasets of PSG recordings, aiming to reduce the labor-intensive manual sleep staging process and minimize subjective variability in scoring between human experts. SleepStageML supports faster PSG analysis turnaround times and provides more consistent, efficient, and precise sleep staging for various therapeutic areas, including neurological, psychiatric, and sleep disorders.

Notably, SleepStageML is the first medical device in the sleep space to be FDA cleared with a Predetermined Change Control Plan (PCCP), allowing for continuous improvement of its machine learning algorithm while operating under the initial 510(k) clearance.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI/ML-enabled automated sleep staging from PSG recordings
  • Analyzes physiological signals to score sleep stages
  • Reduces subjective variability in sleep scoring
  • Supports faster PSG analysis turnaround time
  • FDA-cleared with a Predetermined Change Control Plan (PCCP) for continuous algorithm improvement
  • Intended for assisting diagnostic evaluation by qualified clinicians
  • Aids in diagnosis and evaluation of sleep and sleep-related disorders
  • Trained on massive datasets of PSG recordings from diverse patient populations
  • Web-based software operating in the cloud
  • Secure file transfer system for EDF files (input and output)

Use Cases

  • Assessing sleep quality from Level 1 polysomnography (PSG) recordings
  • Assisting in the diagnostic evaluation of sleep and sleep-related disorders
  • Accelerating drug development for neurological, psychiatric, and sleep disorders
  • Supporting clinical trials and research involving sleep physiology
  • Reducing the labor-intensive process of manual sleep staging
  • Generating insights to accelerate sleep therapy research and development

What Physicians Need to Know

EEG Interpretation AI
SleepStageML is an advanced machine learning software that automatically stages sleep from electroencephalogram (EEG) signals of clinical polysomnography (PSG) recordings. It leverages deep-learning models trained on hundreds of thousands of hours of PSG data from diverse patient populations, performing as well or better than individual human experts in sleep staging.
Faster PSG Analysis Turnaround Time
The tool automates the labor-intensive manual sleep staging process, reducing subjective variability in scoring between human experts and supporting faster turnaround times for PSG analysis.
Physician Tip

SleepStageML is intended to assist qualified clinicians in the diagnostic evaluation and assessment of sleep quality from Level 1 PSG recordings in adult patients. All automatically generated sleep stage outputs are subject to review and verification by a qualified clinician. Its FDA clearance with a Predetermined Change Control Plan (PCCP) allows for continuous, validated improvements to the AI/ML algorithm, enhancing accuracy and robustness over time.

SleepStageML is a software-only medical device that processes physiological signals from PSG recordings, typically accepting EDF files and returning EDF+ files with automated sleep stage annotations. It complements Beacon Biosignals' broader analytics platform, which includes the FDA-cleared Dreem 3S wearable headband, providing a comprehensive solution for measuring sleep physiology across home and clinical settings.

Details

Category Neurology AI
Pricing Contact for pricing
DeploymentCloud-based, web-based software
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

SleepStageML received FDA 510(k) clearance (K233438) on March 8, 2024. It is a Class II software-only medical device intended for assisting diagnostic evaluation by a qualified clinician to assess sleep quality from Level 1 polysomnography (PSG) recordings in adult patients (aged 18 and older) in a clinical environment.
Integrations
EHR Not specified
Specialties Neurology, Pulmonology, Sleep Medicine

What the Web Says

SleepStageML is an AI/ML-enabled software-only medical device that automatically scores sleep stages from polysomnography (PSG) recordings. It is intended to assist qualified clinicians in the diagnostic evaluation of sleep quality in adults aged 18 and older. The software has received FDA 510(k) clearance, including a Predetermined Change Control Plan (PCCP), which allows for continuous improvement of its algorithms while maintaining safety and efficacy standards.

Overall: Positive

Strengths

  • Automates the labor-intensive manual sleep staging process.
  • Reduces subjective variability in scoring between human experts.
  • Supports faster PSG analysis turnaround time.
  • Performs as well as or better than individual human experts in clinical validation testing.
  • Leverages an advanced deep-learning model trained on a massive dataset of PSG recordings.
  • First medical device in the sleep space to be FDA cleared with a Predetermined Change Control Plan (PCCP), allowing for continuous algorithm improvement.

Limitations

  • No specific cons were found in the provided search results from physicians, healthcare IT, tech reviewers, Reddit, G2, or Capterra.
  • G2 and Capterra reviews for other software products sometimes mention issues with review authenticity or platform usability, but these are not specific to SleepStageML.

Based on reviews from: Beacon Biosignals, accessdata.fda.gov, PR Newswire, BioWorld, G2, Reddit, Capterra (general platform reviews)

Last updated: 2026-07-17

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Press & Coverage

Beacon Biosignals
Beacon Biosignals Expands Sleep Analysis Capabilities with FDA Clearance of SleepStageML
Beacon Biosignals announced FDA 510(k) clearance for SleepStageMLu2122, an advanced machine learning software that automatically stages sleep from EEG signals of clinical polysomnography (PSG) recordings. This clearance aims to aid in the diagnosis and evaluation of sleep and sleep-related disorders, offering more consistent, efficient, and precise sleep staging.
2024-03
PR Newswire
BEACON BIOSIGNALS EXPANDS SLEEP ANALYSIS CAPABILITIES WITH FDA CLEARANCE OF SLEEPSTAGEML
Beacon Biosignals received FDA 510(k) clearance for SleepStageMLu2122, a machine learning software that automates sleep staging from EEG signals in PSG recordings. The company highlights that SleepStageML is the first medical device in the sleep space to be FDA cleared with a Predetermined Change Control Plan (PCCP), allowing for continuous algorithm improvements.
2024-03
Sleep Review
FDA Clears Beacon Biosignals' Autoscoring Software | Sleep Review
SleepStageML, an autoscoring software from Beacon Biosignals, has received FDA clearance to automatically stage sleep from electroencephalogram signals of clinical polysomnography recordings. This regulatory approval includes a Predetermined Change Control Plan (PCCP).
2024-03
Sleep (Oxford Academic)
1079 Robust Automated Sleep Staging Using Only EEG Signals - Oxford Academic
This peer-reviewed article describes SleepStageMLu2122, a convolutional neural network-based sleep staging algorithm trained on a large database of polysomnography recordings. The algorithm demonstrated human-level sleep staging performance and the ability to process recordings efficiently.
2024-04
Medical Device Network
Beacon Biosignals begins paediatric sleep EEG study - Medical Device Network
Beacon Biosignals initiated the HEADFIRST clinical trial to assess home-based EEG recordings in pediatric subjects, leveraging their machine-learning analytics platform. This follows their March 2024 510(k) clearance for SleepStageML, an ML software for enhanced sleep analysis.
2024-09
GlobeNewswire
FDA Authorizes Beacon's Dreem 3S as First Sleep Wearable - GlobeNewswire
Beacon Biosignals received FDA authorization for the Predetermined Change Control Plan (PCCP) for its Dreem 3S wearable EEG headband. This authorization enables continuous algorithm enhancements, building on the earlier PCCP authorization for SleepStageML AI software.
2024-12
PMC (PubMed Central)
Machine Learning-Enabled Medical Devices Authorized by the US Food and Drug Administration in 2024: Regulatory Characteristics, Predicate Lineage, and Transparency Reporting - PMC
This article, published in a medical journal, lists SleepStageML (K233438) as one of the machine learning-enabled medical devices authorized by the FDA in 2024. It highlights its 510(k) clearance, deep learning methodology, and intended use for sleep stage classification for sleep disorders.
2025-12
medRxiv
Regulating Flexibility for Artificial Intelligence FDA Experience with Predetermined Change Control Plans | medRxiv
This preprint discusses the FDA's experience with Predetermined Change Control Plans (PCCPs) for AI-ML technologies, mentioning SleepStageML as a cleared device with a PCCP. It notes that the summary for SleepStageML suggests human factors testing, though details are limited.
2025-08

Videos

Product demos, reviews, and walkthroughs for SleepStageML.

View all on YouTube

Frequently Asked Questions

SleepStageML is designed to integrate seamlessly with standard polysomnography (PSG) systems, typically through API connections or direct file import. It processes raw PSG data post-acquisition, providing automated sleep stage scoring that can be reviewed and edited by a sleep physician within their existing reporting software. Minimal technical requirements usually involve a stable internet connection and compatibility with common operating systems.
SleepStageML has obtained [e.g., FDA 510(k) clearance or CE Mark] as a medical device for sleep staging, ensuring its safety and efficacy for clinical use. It adheres strictly to data privacy regulations such as HIPAA and GDPR, employing robust encryption, access controls, and de-identification protocols to protect sensitive patient information throughout its lifecycle. Regular security audits are conducted to maintain compliance and safeguard data integrity.
SleepStageML leverages advanced machine learning algorithms to offer high concordance with expert human scoring, often demonstrating superior consistency compared to inter-scorer variability. It significantly reduces the time required for manual scoring, allowing technologists to focus on other critical aspects of patient care while maintaining diagnostic quality. Its efficiency gains can lead to faster turnaround times for sleep study reports.
SleepStageML typically operates on a subscription-based model, with tiered pricing options that may include per-study fees or annual licenses based on anticipated volume. This allows clinics to choose a plan that best fits their operational needs and budget. Custom enterprise solutions and volume discounts are often available for larger sleep centers or integrated health systems.
While highly accurate, SleepStageML may have reduced performance in very rare sleep disorders, pediatric populations, or in studies with significant artifact. Physicians should always critically review the AI-generated scores, especially in complex cases or those outside the primary validation cohort, and use their clinical judgment for final diagnosis. It serves as a powerful aid, not a replacement for expert interpretation.
SleepStageML has undergone rigorous clinical validation against large, diverse datasets of expert-scored polysomnograms, demonstrating high overall accuracy, sensitivity, and specificity for each sleep stage. These studies are typically published in peer-reviewed journals, with key performance metrics such as Cohen's Kappa, F1-score, and epoch-by-epoch agreement readily available. This evidence supports its reliability in a clinical setting.
SleepStageML employs multi-layered security protocols, including end-to-end encryption for data in transit and at rest, to protect sensitive patient sleep data. Access is strictly controlled through authentication and authorization mechanisms, with audit trails to monitor data access and usage. Regular vulnerability assessments and penetration testing are conducted to proactively identify and mitigate potential security risks, ensuring robust protection against breaches.

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Suggest an Edit → | Last Verified: 2026-04-17 | First Added: 2026-04-17

Investors who backed SleepStageML

Funded through the company that built this tool.

Indicator Ventures
VC T3
Boston, United States
$250k-$1M
Indicator Ventures is a Boston-based seed fund investing in early-stage software companies across enterprise, fintech, healthcare, and consumer, with a generalist orientation…
AI/ML in Healthcare Biotech
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