Wearables are a cool tool to track and measure sleep in scientific studies!
The first, and most well-established, source of health data comes from monitoring sleep and physical activity patterns using a trusted consumer wearable device. This method gives you substantial insights into your sleep and activity levels, and the tools provided allow you to enhance both.
Here, we feature some of SCL's work showing how we’ve validated these methods specifically in Singapore and the insights gained from these studies.
#1
HERE, we show that wearable sleep trackers can rival or exceed the performance of research actigraphs (which cost up to 3-5 times more!) in assessing sleep timing, duration, and regularity. This finding can inform the type of sleep tracker research groups purchase for long term ambulatory measurement of sleep.
#2
However, there are caveats: on average, the accuracy of these trackers fall with user age and with persons with less efficient sleep (either longer sleep latency or greater wake after sleep onset). This FINDING is of practical importance to persons who take sleep tracking seriously.
#3
Not all ‘consumer wearables’ are comparably accurate. Low-cost OEM devices made by putting together sensors and off the shelf algorithms without evidence for testing or refinement, perform poorly. These FINDINGS are an important consideration for programs that use a mix of good quality and low-cost sleep trackers, for example, in population health studies.
#4
One of the sources of inaccuracy in sleep measurement relates to misclassification of periods of quiet wakefulness as sleep. In this STUDY, our team devised a protocol to test this in a realistic manner that should be incorporated into future testing protocols. We showed how this protocol can be used to differentiate better quality and lower quality trackers. This testing protocol may be used by future researchers seeking to evaluate in wearable sleep trackers in realistic settings.
#5
HERE, we showed how the photoplethysmogram (PPG) waveform signal, changes according to sleep stage, reflecting greater parasympathetic influence at work during N3 sleep compared to light sleep and REM. The waveform recorded in N3 sleep is also associated with measures that correspond to relatively lower arterial stiffness. This provides additional evidence of the benefit of N3 sleep duration.
#6
In this STUDY, we used large scale data to show that observation periods longer than 1 week (up to 18 days) are necessary to achieve ~80% confidence in assessing sleep regularity.