Sleep Arousal Disorders

This milestone marks a significant expansion of Beacon's analysis platform, extending its application from at-home sleep monitoring to comprehensive coverage of traditional in-lab polysomnography (PSG). The software, developed by Beacon Biosignals, automatically stages sleep from electroencephalogram (EEG) signals of clinical PSG recordings. This advancement promises to aid in the diagnosis and evaluation of sleep and sleep-related disorders, offering a more consistent, efficient, and precise method for sleep staging in therapeutic areas such as neurological, psychiatric, and sleep disorders. “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, 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." Therapies for sleep disorders The software uses advanced deep-learning models trained on extensive datasets containing hundreds of thousands of hours of PSG recordings. These datasets encompass a diverse range of individuals, including healthy subjects and patients with various sleep disorders, neurological diseases, and psychiatric conditions. Clinical validation testing has demonstrated that SleepStageML performs comparably to or even outperforms individual human experts, as reported in literature. googletag.cmd.push(function () { googletag.display('text-ad1'); }); Key benefits include automating the labor-intensive manual sleep staging process, reducing subjective variability in scoring between human experts, and supporting faster PSG analysis turnaround time. Brandon Westover is Landau Professor of Neurology at Harvard Medical School and co-founder of Beacon Biosignals. Development for sleep-related disorders He said: “The advanced machine learning algorithms powering SleepStageML reduce human scoring variability and increase precision of sleep measurements. “This automated approach unlocks new clinical insights to drive forward therapy development for sleep and sleep-related disorders.” An additional notable aspect is its designation as the first medical device within the sleep space to be FDA-cleared with a Predetermined Change Control Plan (PCCP). This regulatory pathway allows Beacon to continuously improve the sleep staging machine learning algorithm while operating under the initial 510(k) clearance. The Predetermined Change Control Plan outlines strict validation testing criteria for any updates to the AI/ML model, ensuring improved performance compared to the originally cleared version. Robust sleep staging capabilities “SleepStageML’s approved PCCP is a game-changing development for the sleep field,” said Alexander Chan, 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.” The company says FDA clearance for SleepStageML represents a significant milestone for the company, bolstering its 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.

MILESTONE BROADENS THE COMPANY'S ANALYSIS PLATFORM, EXTENDING ITS APPLICATION FROM AT-HOME SLEEP MONITORING TO ALSO INCLUDE COMPREHENSIVE COVERAGE OF TRADITIONAL IN-LAB POLYSOMNOGRAPHY. BOSTON, March 27, 2024 /PRNewswire/ -- 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 . 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 . To work together, visit . Follow us on Twitter (@Biosignals) or LinkedIn (). For media inquiries, please contact [email protected]. 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. SOURCE Beacon Biosignals

New research reveals that neurons in the preoptic hypothalamus -- the region of the brain that regulates sleep and body temperature -- are rhythmically activated during non-rapid eye movement sleep (NREM). Stress activates these brain cells out of turn, causing 'microarousals,' that interrupt sleep cycles and decrease the duration of sleep episodes, according to new research. New research reveals that neurons in the preoptic hypothalamus -- the region of the brain that regulates sleep and body temperature -- are rhythmically activated during non-rapid eye movement sleep (NREM). Stress activates these brain cells out of turn, causing "microarousals," that interrupt sleep cycles and decrease the duration of sleep episodes, according to research from Perelman School of Medicine at the University of Pennsylvania, published today in Current Biology. While our bodies are at rest when we are asleep, our brains are still very active during four different stages of sleep. In each 90-minute sleep cycle, there are three stages of NREM sleep, and one stage of rapid eye movement (REM) sleep. During the first two stages of NREM sleep, brain waves, heartbeat, and breathing slow, and body temperature decreases. Stage two also includes unique brain activity, called spindles and K-complexes, which are short bursts of activity responsible for processing outside stimuli, as well as for consolidating memory. Stage three of the NREM sleep cycle is when the body releases growth hormone, which is important for repairing the body, keeping the immune system healthy, and further improving memory. During phase three, brain waves are larger, called delta waves. REM sleep, which happens in this phase when dreaming normally occurs, is also critical for memory formation, emotional processing, and brain development. "When you have a bad night of sleep, you notice that your memory isn't as good as it normally is, or your emotions are all over the place -- but a bad night of sleep interrupts so many other processes throughout your body. This is even more heightened in individuals with stress-related sleep disorders," said senior author, Shinjae Chung, PhD, an assistant professor of Neuroscience. "It's crucial to understand the biology driving the brain activity in these crucial stages of sleep, and how stimuli like stress can disrupt it, so that we might someday develop therapies to help individuals have more restful sleep that allows their brain to complete these important processes." The researchers monitored the activity in the preoptic area (POA) of the hypothalamus of mice during their natural sleep and found that glutamatergic neurons (VGLUT2) are rhythmically activated during NREM sleep. They also found that VGLUT2 neurons were most active during wakefulness, and less active during NREM and REM sleep. During microarousals in NREM sleep, VGLUT2 neurons were the only active neurons within the POA, and their signals started to increase in the time before a microarousal. To confirm that active VGLUT2 neurons were indeed the cause of microarousal, the researchers stimulated the VGLUT2 neurons in sleeping subjects, which immediately increased the amount of microarousals and wakefulness. Next, to illustrate the connection between stress and increased VGLUT2 neuron activation, researchers exposed subjects to a stressor, which increased awake time and microarousals, and decreased overall time spent in REM and NREM sleep. Researchers also noted increased VGLUT2 neuron activity during NREM sleep in the stressed subjects. What's more, when researchers inhibited VGLUT 2 neurons, microarousals during NREM sleep decreased, and NREM sleep episodes were longer. "The glutamatergic neurons in the hypothalamus give us a promising target for developing treatments for stress-related sleep disorders," said first author, Jennifer Smith, a graduate researcher in Chung's lab. "Being able to reduce interruptions during the important stages of non-REM sleep by suppressing VGLUT2 activity would be groundbreaking for individuals struggling with disrupted sleep from disorders like insomnia or PTSD." This research was supported by the National Institute of Neurological Disorders and Stroke (R01NS110865).