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Home » Explore All » How AI Can Improve Your Health While You Sleep
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HOW AI CAN IMPROVE YOUR HEALTH WHILE YOU SLEEP

October 12, 2021 Adam Kimmel


 



Image Source: Archi_Viz/Shutterstock.com

By Adam Kimmel for Mouser Electronics

Published October 12, 2021


INTRODUCTION

AI is transforming nearly every aspect of healthcare and assists in many
applications. From reducing the time physicians take to diagnose diseases to
autonomously managing the medical device supply chain, AI removes the lag humans
need to realize, process, and react to changes in conditions. The technology
processes data increasingly fast. Coupled with the IoT and increased
connectivity, AI is constantly using data to assess—and improve—the quality of
the application it serves.

An emerging application for AI has been assisting with sleep tracking,
monitoring, and improvement. Optimizing sleep carries many benefits, such as
higher productivity, a better immune system and heart health, and overall
happiness. More, a lack of proper sleep not only causes grogginess, but can also
result in the development of diabetes, cause weight gain and high blood
pressure, weaken the immune system, and increase the risk of heart disease,
among other issues. While pursuing the best rest possible is worth the effort,
there is a significant technology advancement needed to deliver that result. To
understand how technology can enhance sleep, we need to review the sleep stages
and how the body uses rest to determine how AI can improve them.


STAGES OF SLEEP

Sleep, as a bodily process, is rooted in neuroscience. Though seemingly akin to
autopilot, sleep is an active brain process. This is significant in that any
enhancement or change to the sleep cycle must not interfere with the brain's
active work to be effective. To know the best way to engage, scientists have
used EEGs, MRIs, and other tools to map out discrete sleep states and create the
baseline condition.

Sleep activates a series of neural networks in unique ways over four distinct
phases:

 * Sleep stage 1: N1 (1-5 min)
 * Sleep stage 2: N2 (10-60 min)
 * Sleep stage 3: Slow-Wave Sleep (SWS, 20-40 min)
 * Sleep stage 4: Rapid Eye Movement (REM) Sleep (10-60 min)

Of these stages, Slow-Wave Sleep (SWS) lasts about 20-40 minutes per cycle and
is the deepest stage of sleep. SWS is followed by Stage 4, Rapid Eye Movement
(REM), a reasonably active sleep period that studies show may help with memory
and performance. Together, these four stages last roughly 90 minutes. The
subject experiences optimum benefits when they fully complete these cycles. In
other words, benefits are not achieved when sleep processes are interrupted.

The cycle definitions also explain why it is essential to get 7-8 hours of
sleep. At that duration, the body processes the complete sleep cycle five total
times. The problem is when those five cycles are not optimized. Unaltered, the
subject having problems with sleep is not getting the full benefit of this
critical bodily process. Even without a whole night’s sleep, customizing the
experience makes any amount of sleep they can get more beneficial. With that in
mind, how does the technology work?


HOW TECHNOLOGY ENHANCES SLEEP

Sensors are the starting point for any AI application. Measuring everything from
heart rate to motion and sound, sensors collect and feed data back to the
cloud-based processor, which uses AI to monitor the data over time. This data
provides insights into trends and patterns in the subject’s sleep habits,
eventually enabling the technology to predict the sleep cycle timing. Like any
regression-based process, the more data the processor has to work with, the more
accurate its prediction. Once the AI technology processes enough sleep data,
engineers establish an individual sleep cycle for the subject.


MONITORING THE INITIAL SLEEP CONDITION

Once the algorithms identify a unique sleep cycle, the AI can work to optimize
the sleep process in various ways. One of the first approaches is to time sleep
cycles to avoid waking mid-cycle, especially during slow-wave sleep. Awakening
during State 3 often makes the subject feel groggy and over-tired. Here is an
example of how this would change the traditional method of waking up:

> Imagine you need to wake up at 7 am. With a regular alarm clock, you set it
> for 7 am precisely. However, if a device tracked your sleep to wake you up at
> the optimum time during the cycle, it would wake you up after completing the
> last ~90 min cycle that ends before your designated wake-up time. As a result,
> even though you wake up earlier, you will likely feel more rested than you
> would sleeping longer because you woke post-cycle. While a conventional alarm
> clock would not know this, AI can ensure that it syncs the alarm function to
> your unique cycle.


SLEEP AUDITING

Another way AI can enhance sleep is to identify factors that may be interrupting
sleep during the night. These factors can exist as environmental or potential
health factors, which engineers can discover by monitoring the heart and lungs.
The most important outcome of AI-enhanced sleep is to ensure that the sleep
environment is conducive to remaining asleep during the night, especially during
active cycling. Some control levers AI can affect are maintaining light/dark
cycles with blind/shade control. This approach leverages the body’s desire
to sync to a Circadian cycle with smart [Circadian] lighting, helping the body
feel alert during periods of light and tired when it is dark in the sleeping
room.

Additional mechanisms to enhance sleep are temperature control and noise
control. The existing data, taken over a sufficiently long time, can consider
the body's response to thunder or other noise events during sleep and alter
conditions accordingly. Technology can even be applied in shared-bed situations
to make “smart pillows” that connect to the shared devices to vibrate as a
wake-up alarm for only one partner.


AI CAN AID IN SLEEP DISORDER DIAGNOSIS

In addition to helping subjects improve their sleep quality, AI can help
physicians and medical professionals diagnose sleep disorders. Sleep disorders
are an increasingly common challenge across the world and are linked to severe
illness and death. One of the principal dangers of prolonged sleep deprivation
is that it can lead to sleep disorders.

The objective of a sleep analysis is to collect and process enough information
through sleep-staging to uncover trends that indicate a disorder. For example,
the University of Copenhagen (Denmark) has developed a neural network called
U-Sleep, a publicly available sleep-staging AI platform. Scientists collected
baseline information through a study with 15,000 participants, which provided a
comprehensive matrix of data they can use to compare with the signatures of
known sleep disorders. For example, sleep experts can compare a pattern of
oxygen level changes or breathing stoppages with sleep apnea, insomnia, and
other illnesses to uncover a condition. Better yet, the predictive ability of AI
can extrapolate a pattern observed in advance of a presenting symptom and
discover an issue before it occurs.


TAKEAWAY

AI is transforming the human experience, helping to provide benefits to improve
the overall quality of life. For example, it can monitor initial sleep
conditions, map and audit the sleep stages, and quietly customize the local
environment in the sleep location to the subject’s preference. As a result, AI
can enhance the sleeping experience while preserving the sleep cycle and
diagnosing and predicting sleep disorders, improving attention, alertness, and
health.


> ABOUT THE AUTHOR
> 
> Adam Kimmel has nearly 20 years as a practicing engineer, R&D manager, and
> engineering content writer. He creates white papers, website copy, case
> studies, and blog posts in vertical markets including automotive,
> industrial/manufacturing, technology, and electronics. Adam has degrees in
> Chemical and Mechanical Engineering and is the founder and Principal at ASK
> Consulting Solutions, LLC, an engineering and technology content writing firm.
> 
> More Content by Adam Kimmel

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