HOUSTON, June 5, 2024
/PRNewswire/ -- Fullpower Technologies, in collaboration with
Stanford Sleep Medicine and UCSF
Department of Psychiatry and Behavioral Sciences, presented two
major studies at the SLEEP 2024 conference, furthering our
understanding of sleep fragmentation and heart rate variability
(HRV) during sleep. These studies utilized the advanced
Sleeptracker-AI® Monitor, showcasing the solution's
ability to gather extensive data and offer valuable insights into
sleep health.
"We are proud of our continued collaboration in advancing Sleep
Science research with Stanford Sleep
Medicine and UCSF. Together, we are sharing these new
findings with the sleep research community leveraging the
Sleeptracker.ai platform and network of sleepers," said
Philippe Kahn, CEO of
Fullpower.ai.
Study on Sleep Fragmentation in a Large US Sample
The first study, led by Dr. Clete
Kushida from Stanford
University, investigated sleep fragmentation across
different age groups and genders using Sleeptracker-AI®
data from over 117,000 participants and over 10 million recorded
nights. The Sleeptracker-AI® Monitor's noninvasive,
under-mattress sensors provided reliable data on arousals and
sleep-disordered breathing (SDB).
Key findings include:
- Greater Sleep Fragmentation in Men: Men exhibited
significantly higher sleep fragmentation during REM sleep compared
to women across all ages above 24. However, fragmentation decreased
with age after 34.
- Age-related Differences: Sleep fragmentation increased
with age during NREM sleep for both genders but showed a complex
pattern during REM sleep, initially increasing up to 25-34 years
and then decreasing with age.
These results highlight the potential of home monitoring devices
in identifying sleep disturbances and their variations across
demographics, emphasizing the need for further research to
understand the underlying mechanisms.
Study on Heart Rate Variability (HRV) During Sleep
The second study, led by Dr. Yue Leng from the University of California, San Francisco, examined
HRV in over 38,000 individuals, focusing on the impact of
obstructive sleep apnea (OSA). Using the
Sleeptracker-AI® Monitor, the study collected HRV data
from 2.7 million recorded nights.
Key findings include:
- HRV and OSA Severity: Individuals with moderate to
severe OSA had significantly higher overall HRV variability (SDNN)
and lower parasympathetic activity (RMSSD) than those without OSA.
These differences were more pronounced in middle-aged adults.
- Age and Gender Differences: Both HRV metrics decreased
with age. SDNN was consistently lower in females, while RMSSD
showed greater reductions in individuals with severe OSA,
particularly among younger and middle-aged adults.
This study underscores the importance of continuous, noninvasive
monitoring of HRV to understand its relationship with sleep
disorders and autonomic nervous system balance.
Conclusion
Fullpower Technologies' participation in SLEEP 2024 highlights
the impactful research facilitated by the
Sleeptracker-AI® platform. These studies demonstrate the
solution's capability to gather large-scale, real-world data,
offering valuable insights into sleep health and paving the way for
improved sleep disorder diagnostics and personalized treatment
approaches.
For more information on these studies and the
Sleeptracker-AI® platform, please visit
sleeptracker.ai
About Fullpower Technologies
Fullpower-AI® is the provider of a generative AI
deep-learning biosensing platform. The Fullpower-AI®
platform is a remote real-time biosensing edge-to-cloud solution
vetted and successfully deployed in 60+ countries.
Fullpower-AI® customers are in sleep, life sciences,
health, wellness, and biotechnology. A portfolio of 135+ patents
backs the platform. Fullpower-AI® is ISO 27001
certified.
For more information, contact BusDev@fullpower.com
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