Results from Sleep Number’s first study
accepted for publication demonstrate potential for the 360 smart
bed to detect sleep stages in real-time, which could help guide
intervention for certain sleep disorders in the future
Additional studies demonstrate the research
capabilities of the 360 smart bed to predict and detect symptoms of
influenza-like illnesses and to study sleep disorders, such as
insomnia
Sleep Number to host symposium on the
optimization of sleep environments for improved sleep quality, led
by world leaders in sleep research
Sleep Number Corporation (Nasdaq: SNBR), the sleep
health, science, research and innovation leader, will announce new
studies using its 360® smart bed at World Sleep 2022, the 16th
international meeting of the World Sleep Society in Rome from March
11-16. Sleep Number will present results of its first study
accepted for publication, which will appear in the journal
Physiological Measurement, showing the potential of an algorithm to
detect sleep stages in real-time using cardiac data gathered from
its 360 smart bed. Additionally, Sleep Number will present results
of a prediction model for influenza-like illnesses and a study to
potentially detect sleep disorders like insomnia. These studies
further demonstrate the potential research capabilities of the 360
smart bed to accurately assess and monitor sleep in a non-invasive,
longitudinal way, while also delivering effortless, proven quality
sleep. Sleep Number will also host a symposium with world-leading
sleep experts to evaluate how factors like temperature, light,
noise and sleeping position can be optimized to improve sleep
quality.
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Sleep Number Corporation, the sleep
health, science, research and innovation leader, announced new
studies using its 360® smart bed at World Sleep 2022, the 16th
international meeting of the World Sleep Society in Rome from March
11-16. (Graphic: Business Wire)
“As evidenced by our new data presented at World Sleep 2022 and
our first study accepted for publication, Sleep Number is
redefining the standards for monitoring sleep for research and
health through the 360 smart bed,” said Annie Bloomquist, Chief
Innovation Officer, Sleep Number. “In collaborating with leading
physicians, researchers and institutions, we know they need a
trusted device that’s accurate and offers longitudinal data
collection. They seek the ability to understand native,
undisturbed, real-world sleep behaviors and their ensuing health
implications to translate scientific understanding into improved
sleep quality. Our 360 smart bed offers those capabilities. We are
proud to advance the development of meaningful sleep health
innovations and provide actionable, evidence-based solutions to
achieving quality sleep to a global audience. This reflects Sleep
Number’s commitment to improve society through higher quality
sleep.”
Real-time implementation of sleep staging using interbeat
intervals
- In this study, which was accepted for publication in the
journal Physiological Measurement, Sleep Number demonstrated that
nightly sleep stages could be accurately predicted using data from
cardiac signals as compared to traditional brain wave signals. The
results indicate that, in the future, the 360 smart bed may be able
to detect the risk of sleep apnea.
In normal heart function, each value between two heart beats,
known as heart interbeat intervals (IBIs) varies from beat to beat.
This natural variation is known as HRV. IBIs can change rapidly
during sleep, enabling the measurement of sleep stages in real-time
through algorithms that utilize cardiac metrics. However, these
traditional algorithms can range in accuracy and typically include
numerous parameters or utilize entire sleep sessions for
classification, making them not suitable for real-time
interventions. In this study, Sleep Number developed a small deep
neural network (DNN) algorithm to detect sleep stages using IBIs
measured through ECG. ECG data from healthy sleepers and people
with sleep apnea were used to train and validate the algorithm.
Results of the study showed the Sleep Number algorithm performed
with high specificity and moderate sensitivity in detecting deep
and REM sleep. The algorithm performed better overall in healthy
sleepers compared to those with sleep apnea, likely due to
differences in IBIs seen between the two groups. These results
suggest this algorithm can be used to perform real-time sleep
staging and potentially direct intervention strategies during REM
or deep sleep.
Approximation of Influenza-like illness rates using sleep and
cardiorespiratory data from a smart bed
- This study investigated whether Sleep Number’s COVID-19
prediction model could be applied to detect symptoms of other
influenza-like illnesses (ILI) by comparing pre-pandemic smart bed
sleeper data to U.S. Centers for Disease Control and Prevention
(CDC) trend reports on ILI rates. The findings indicate that, in
the future, the 360 smart bed may be able to predict and track the
development of symptoms associated with a wide range of respiratory
illnesses and notify sleepers prior to symptom onset.
Viral respiratory illnesses such as influenza can have an impact
on sleep quality, duration and cardiorespiratory function.
Previously, Sleep Number developed a symptom detection model to
predict COVID-19 infection using real-world, unobtrusive sleep
metrics gathered from its 360 smart bed users. Inputs to the
detection model that were obtained using ballistocardiograph
signals from the smart bed included sleep duration, sleep quality,
restful sleep duration, time to fall asleep, respiration rate,
heart rate and motion level.
The sleep data of 4,187 sleepers from January 2017 to December
2019 were included in the study. Data from January 2017 to June
2018 were fitted to weekly ILI rates reported by the CDC to train
the prediction model, and correlation coefficients between
predicted and reported ILI rates between July 2018 and December
2019 were calculated. The study showed a correlation of 0.91
between ILI symptoms predicted with the Sleep Number model and
CDC-reported rates. Coefficients close to 1.0 indicate a positive
correlation. In addition, when analyzing the 2018-2019 influenza
season specifically, the correlation of predicted and reported ILI
rates was 0.87.
The sleep metrics measured by the 360 smart bed are a unique
source of real-world longitudinal data collected in an unobtrusive
manner. These results demonstrate the potential for the Sleep
Number model to predict and track the development of symptoms
associated with a wide range of respiratory illnesses, including
influenza and COVID-19.
EEG spectral properties and associated ECG-based heart rate
variability in people with insomnia versus healthy sleepers
- Sleep Number found that important sleep characteristics of
insomnia that are traditionally measured by brain wave activity via
an electroencephalogram (EEG), can be captured utilizing cardiac
signals measured by the 360 smart bed. The results suggest that, in
the future, the 360 smart bed may be able to detect a risk of
insomnia by using cardiac data, without a sleeper having to
participate in a formal sleep lab study.
Sleep disorders such as insomnia may disrupt normal central and
autonomic nervous system function, meaning they can affect the way
the brain operates and the unconscious regulation of essential
bodily functions including breathing, heart rate, blood pressure
and others. These disruptions can be measured by coupling EEG
readings, which analyze brain waves, and electrocardiogram (ECG)
readings, which analyze cardiac activity, with heart rate
variability (HRV). This study was conducted to compare the sleep
architecture (rapid eye movement [REM] sleep and non-REM sleep),
central and autonomic nervous system functions and EEG/ECG coupling
of healthy sleepers versus people with insomnia using
polysomnography.
The study showed that people with insomnia exhibited certain
brain waves during non-REM sleep, which is likely a sign of
restlessness and could negatively impact sleep quality. In
addition, the study found these brain waves, measured by EEG, could
be predicted through HRV changes measured by ECG.
Symposium: Can the sleeping environment be optimized to
improve sleep quality?
Environmental factors play a significant role in achieving
quality sleep. On Monday, March 14, Sleep Number’s symposium will
evaluate temperature sensing; the impact of light exposure on sleep
and circadian rhythms as well as the impact of ambient noise on
sleep quality; and the benefits of optimizing sleeping position in
people with sleep disorders that impact breathing.
The symposium panel includes several world leaders in sleep
research:
- Eve Van Cauter, Ph.D.: Frederick H. Rawson Professor and
Director of the Sleep, Metabolism and Health Center at the
University of Chicago; Sleep Number Scientific Advisory Board
member
- Virend Somers, M.D., Ph.D.: Professor of Medicine at
Mayo Clinic College of Medicine and Science; Director of the
Cardiovascular Facility and the Sleep Facility Center for Clinical
and Translational Science at Mayo Clinic; Sleep Number Scientific
Advisory Board member
- Eus van Someren, Ph.D.: Professor at Vrije Universiteit
Amsterdam and Head of the Department of Sleep and Cognition at the
Netherlands Institute for Neuroscience
- Christian Cajochen, Ph.D.: Professor and Head of the
Centre for Chronobiology at the University of Basel
To view our studies and learn more about our innovations in
sleep health, science and research, visit:
www.sleepnumber.com/science.
About Sleep Number
Individuality is the foundation of Sleep Number. Our purpose
driven company is comprised of over 5,000 passionate team members
who are dedicated to our mission of improving lives by
individualizing sleep experiences. We have improved nearly 14
million lives and are positively impacting society’s wellbeing
through higher quality sleep.
Our award-winning 360® smart beds are informed by science. They
learn from over one billion sleep sessions of highly-accurate, real
world sleep data – the cumulation of almost 14 billion hours’ worth
- to automatically adjust to each sleeper and provide effortless
comfort and proven quality sleep. Our 360 smart beds deliver
individualized sleep health reports and insights, including a daily
SleepIQ® score, and are helping to advance meaningful sleep health
solutions by applying sleep science and research.
For life-changing sleep, visit SleepNumber.com or one of our 650
Sleep Number® stores. More information is available on our newsroom
and investor relations sites.
Forward-looking Statements
Statements used in this news release relating to future plans,
events or performance such as plans to expand our capabilities to
predict and detect symptoms of influenza-like illnesses and to
study sleep disorders, such as insomnia, and analyze real-time
sleep staging to potentially detect and guide intervention for
sleep disorders are forward-looking statements subject to certain
risks and uncertainties. Additional information concerning these
and other risks and uncertainties is contained in the company’s
filings with the Securities and Exchange Commission (SEC),
including the Annual Report on Form 10-K, and other periodic
reports filed with the SEC. The company has no obligation to
publicly update or revise any of the forward-looking statements in
this news release.
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Julie Elepano Sleep Number Public Relations
Julie.Elepano@sleepnumber.com
Nichole Teixeira Sleep Number Public Relations
Nichole.Teixeira@sleepnumber.com
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