Instrumentation & Measurement Magazine 24-2 - 30

Internet of Things for
Sleep Monitoring
Dominic J. Jaworski, Aerin Park, and Edward J. Park

T

he Internet of Things (IoT) technologies, including
wearables and non-wearables, enable and facilitate
continuous sleep monitoring in a completely unobtrusive manner. This paper presents an overview of such
technologies with a prototype IoT sleep tracking platform as
an experimental demonstration. Such IoT sleep devices, which
measure physiological and/or environmental parameters
non-intrusively, may help individuals optimize their sleep location and environment to get the most rest and improve their
health and quality of life. Overall, this paper demonstrates the
feasibility of conducting an IoT-based at-home sleep study and
assists in planning for future IoT-based sleep studies.

Measurement of Sleep Stages
Sleep is important for one's daily life as it allows the body to
rest and recover from daily activities. Sleep quality is a good
indicator of individual health and can be directly related to various illnesses and health related issues [1]. The gold standard
to measuring sleep is known as polysomnography (PSG)-it
measures many physiological signals such as electroencephalogram (EEG), electrocardiogram (ECG), electrooculogram
(EOG), electromyogram (EMG), respiration, and pulse oxygen
[2]. Sleep is scored through rules and guidelines established by
the American Academy of Sleep Medicine (AASM) with stages
ranging from wake to sleep stages 1-3 for light and deep sleep,
respectively, and rapid eye movement (REM) sleep [3]. While
a PSG study, which is often performed in a sleep clinic, may be
effective in identifying the sleep stages, the number of sensors
and electrodes that need to be attached to a sleep subject can be
intrusive and disruptive to their sleep quality [4].
Therefore, more convenient alternatives have been developed to estimate sleep through less intrusive methods, such
as actigraphy and ballistocardiography (BCG). Actigraphy
estimates sleep or wake periods by recording and analyzing
limb movements using a wearable activity tracker (or an actigraph) equipped with a microelectromechanical systems
(MEMS) accelerometer. It is a noninvasive technique to evaluate sleep with the devices generally placed on the wrist (they
can also be placed on the ankle, thigh, or trunk) [5]. In recent
30	

years, consumer grade wearables with actigraphy have become readily available through fitness trackers, smartwatches
and smartphones that can measure daily activity for longitudinal studies to analyze daily physical activity levels and sleep/
activity patterns [2]. Since actigraphy does not measure physiological parameters, however, it is not possible to analyze the
specific sleep stages of non-REM and REM. It is therefore limited to estimating differences only between wake and sleep
states, and not among the types of sleep [6].
Recently, BCG has become a viable method for evaluating
sleep by measuring cardiac parameters through body vibrations indirectly from the bed mattress (i.e., non-contact) [7].
At every heartbeat, micro-movements of the body are produced in all three axes in response to cardiac recoil forces from
the blood being pumped through the heart and body [8]. To
accurately sense the body vibrations associated with the heartbeat, a BCG sensor is equipped with a high-resolution tri-axial
MEMS accelerometer. BCG does not measure the activity of
the heartbeat through direct contact electrodes like ECG;
therefore, additional signal processing is required to remove
any movement artifacts from the activity of sleep [7], [8]. While
it is obviously less accurate in identifying the sleep stages
compared to the gold-standard PSG due to the reduced set of
measured physiological parameters [2], the tradeoff lies in its
convenience and unobtrusiveness for continuous sleep monitoring and analysis. More recently, we proposed a combined
use of actigraphy and BCG in order to improve the sleep-wake
classification accuracy [9].
Sleeping patterns are also affected by activities of daily living and the surrounding environment. Known as circadian
rhythms, they are the internal biological clock that regulates sleep and wake during a 24-hour period based on light
and darkness [5]. However, now people have many options
for entertainment and activities at night, including cellular
phone-induced irregular light/sound exposures and nontraditional work schedules (e.g., night shift), that may lead to
the disruption of their normal circadian rhythms. This would
result in what is known as " social jetlag, " which interferes
with their natural sleep cycle [10]. Excessive light exposure

IEEE Instrumentation & Measurement Magazine	
1094-6969/21/$25.00©2021IEEE

April 2021



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