How much should we sleep, and what does the balance between REM and deep sleep look like in those conditions?
At Fullpower Labs, we looked at the data. The Fullpower dataset includes 250 million nights of sleep. Sleep information from the Sleeeptracker Monitor is unique because it is fully contactless and non-invasive, yet still accurate to within 90%+ gold standard polysomnography. Data shows that continuous heart rate averaged throughout the night is minimized with 7.5 hours of sleep. From there, we find that on average, the answer to our question is 10.8% of deep sleep and 25.3% of REM sleep.
At Fullpower Labs, we analyzed our accurate multi-year data-set that comprises 250+ million nights of sleep. We found some interesting seasonal patterns. This infographic shows seasonal changes in heart rate. The Fullpower Sleeptracker platform captures continuous heart rate throughout the night completely non-invasively. Each individual fluctuation in the graph is a weekly max and min, the max being in general weekends (bedtime and wake-time discipline are laxer on weekends) and weekdays with a more disciplined schedule and less “distractions”. This is what we can observe:
Seasonal changes occur with lower heart rates in the summer and higher in the winter. This same pattern was also observed in this independent study in Japan. Our AI-powered analytics discovered this independently and then we found the very interesting Japan paper.
There’s a consistent weekly cycle throughout the year with lower heart rates during the week and higher on the weekends. There’s a significant dip after New Year’s, perhaps due to New Year’s resolutions (better diet, decreased alcohol, more disciplined sleep schedule), but eventually, it fizzles.
This week at Fullpower Labs, we continue to drill down our accurate multi-year data set that comprises 250+ million nights of sleep. We found some new interesting weekly patterns within the previously identified seasonal patterns. This infographic shows weekly zoomed-in in heart rate. The Fullpower Sleeptracker platform captures continuous heart rate throughout the night.
Seasonal changes occur with lower heart rates in the summer and higher in the winter. This same pattern was also observed in this independent study in Japan. Our AI-powered analytics discovered this independently, and then we found the very interesting Japan paper.
Notice week after week, there is a consistent weekly cycle with lower heart rates early in the week leading to higher heart rates on the weekends and then recovery. Interesting.
Let the data speak! This week at Fullpower Labs, we continue to drill down our accurate multi-year data set that comprises 250+ million nights of sleep. We now discovered previously un-identified seasonal patterns correlating continuous Breathe and Heart Rate over a couple of years. The Fullpower Sleeptracker platform captures continuous breath and heart rate throughout the night. See here the weekly fluctuations day-by-day of breathing heart rate and heart rate.
Seasonal changes occur with higher breath rates in the summer and lower in the winter. This is similar to what was observed in this independent study in Japan, where Sleeptracker gives us much more supportive data. Here is the interesting Japan paper.
Our AI-powered analytics discovered these new correlations, and found the "inverse" breath correlations which seem to be published in this post for the first time ever as we couldn't find this science published anywhere! Fascinating power of our long term PSG-grade datasets and tools!
Three years consecutively the data has shown that now that the US has “fallen back” we are likely to see disrupted sleep for two weeks in the Spring. The disruption is a little less in the fall. The Sleeptracker platform is analyzing and “machine learning” anonymized big sleep data during the next few weeks with tens of thousands of sleepers every night. Let the data speak!
At Fullpower Labs, www.fullpower.com this week we were thinking about how much we sleep (and we don't sleep) each individual day of the week on average. So we did some distribution analysis.
Most of our www.sleeptracker.com sleepers have work schedules and are therefore bound by a fixed weekday schedule. Yet there are differences. Of course we tend to replenish our "sleep budget" on weekends. Yet there are statistically meaningful weekday patterns that we represent using the Sleeptracker AI-powered predictive analytics system in the following image!
At Fullpower Labs, https://www.fullpower.com, we are looking at changes in sleep patterns and how they may change over time. With the benefit of the Fullpower medical-grade contactless bio-sensing non-invasive, non-intrusive AI-platform we are able to look at REM sleep, Deep Sleep for example.
This is the first in a series of analysis, looking at age groups. We left out teenagers, for now, as sleep patterns for teens are rather "particular". As we set our sleep goals over this may be an important consideration.
Women and men sleep differently on average. The data seems to show that females may pay more attention to the quality of their sleep. Both genders see a deterioration of their "Sleep Score" when they reach their 40s.
That’s possibly due to societal constraints as well as hormonal changes that are part of the aging process. Then of course, in general, our sleep improves as we age.
The data shows a correlation between heart rate and sleep length. That's the length of actual sleep as opposed to the time spent in bed. This correlation could mean that 6.5 to 8 hours of sleep may be optimal for health. That's because resting heart rate is generally considered a signpost of wellness.
Of course, how those hours slept are broken down into REM and Deep Sleep is a factor. With 250 million nights of sleep analyzed powered by machine learning with Polysomnography-grade accuracy we are learning more every day and happy to share some of that knowledge with the community.
Research shows that other mammals like humans have REM sleep stages and dream. However, cold-blooded animals such as fish and lizards do not. REM is the sleep-stage when we dream and restore our cognition to wake- up more refreshed in the morning.
The data shows a correlation between resting heart-rate and REM sleep. What the data clearly shows is that females tend to get more REM sleep.
The data is in: The Spring time change to DST is the event that is the most disruptive to our sleep in 2019. The methodology that we used to make this determination is by analyzing bedtimes for the days following the time change. Our wake times tend to be fixed due to kid schedules, work schedules, and other obligations. Yet we have some latitude with our bedtime. The later we got to bed, the shorter our sleep opportunity. The data shows that it takes about two weeks in the Spring to get back to balance. That’s very disruptive.
P.S. Personally I hope that this year we stay on DST and do not revert in the fall.