Tracking and Improving My Sleep
Quantified Self organizer and cognitive science researcher, Daniel Gartenberg, is interested in sleep and his passion is this idea of not just tracking sleep but actually being able to improve sleep. He also makes sleep apps. He started tracking his sleep after his business partner contacted him on a recent scientific finding, where basically one could enhance deep sleep auditory stimulation that replicates the frequency of one's own brainwaves when in deep sleep. In this talk, he shares his tips on tracking and improving his sleep.
Galaxy Gear | Hexoskin
My big interest in sleep and my passion is this idea of not just tracking sleep but actually being able to improve sleep. And what inspires me here is maybe if you could just improve sleep a small amount it can have great ramifications for you know everybody’s time.
And what started me on this track was I make sleep apps and Dmitry, my business partner contacted me on this recent scientific finding, where basically you could enhance deep sleep with auditory stimulation that replicates the frequency of your brainwaves when you’re in deep sleep.
So basically how this works is if you can detect when someone is in deep sleep, you play a sound that replicates that delta-wave frequency, and it actually primes and entrenches your brain to have deep sleep.
The issue here is that this happens in very in you know scientific environments with polysomnography and all this technology, my question is can this be applied to an everyday app that people can use.
So I made this app, and basically what it does is that it makes sum assumptions in the fact that you’re most likely to have deep sleep in the first stage of sleep and then it plays this auditory stimulation that replicates that frequency of brainwaves. And what I did is that I tried to test if it actually improves memory, because deep sleep is associated with memory consolidation. So I made this simple app where you do a paired association memory task before you go to bed and then you do it before you wake up and it measures your memory. And you either get no stimulation, 20 minutes of stimulation, or 40 minutes of stimulation and I just randomized on whether or not I got this stimulation at night.
Along with this, first off you have to make sure you are actually getting the stimulation in deep sleep, so I use various devices to measure my sleep, and I’ll get more into my experiences with these devices. I use the Hexoskin to get heartrate, Galaxy Gear, and also something called the Actiwatch.
The sad thing was that the experiment didn’t really work so well. So here you have my performance on the memory task and basically what happened was there is no effect of the stimulation on whether or not that I could remember things. Thus, there is no effect on my sleep efficiency, you know basically the amount of time spent in bed sleeping. So this was kind of sad news, and also I did this task. It’s called the psycho motor vigilance task and that’s a good measure of alertness, and basically if anything the 40 minutes of stimulation was worse for this.
So this was kind of bad news and a little bit disheartening, but it didn’t necessarily mean that the effect doesn’t exist. And one of the reasons why I think I didn’t get the effect was basically because people were aware of this stimulation, even though I have a novel way of giving the stimulation based on if you start moving or not. Forty percent of the time people notice it suggesting that they weren’t in deep sleep when it was administered. So basically it didn’t really work, but my hypothesis is because I didn’t give the stimulation at the right time.
So I started exploring different ways to try to get a non-invasive device that can provide the stimulation at the right time. And I was actually surprised at how much I liked wearing the Actiwatch compared to some of these other devices. So I have over 200 nights of data with the Actiwatch, and the Actiwatch is good because it validated againstpolysomnography for sleep/wake. And out of all the devices it was really the only one that I wasn’t uncomfortable wearing and it also has a really good battery life.
So I’m just going to do a quick overview of a week of that data, and here you’ll see the little dots basically validated sleep/wake, where wake is at the thousand and sleep is at the zero, and the raw activity is in green. And when I went to bed is the blue, and when I woke up is the algorithm to detect is the orange.
And you can really see that when you have this continuous stream of data, which is really the Actiwatch is the only device that provided me this that really jumped out at you like when I was sleeping, and I could evaluate my sleep efficiency pretty accurately with this.
So actually this is an example of bad data. One of the reasons why I didn’t collapse things was sometimes the algorithm didn’t actually detect the right bedtime and wake time. But I kind of confirmed that I already knew about my sleep which is I have pretty good sleep efficiency, 93% that means I have healthy sleep. I’m kind of an night owl because I don’t have a day job and I wake up whenever I want; it’s a nice luxury.
So these are the kind of things that I knew about my sleep. But I really couldn’t glean these from using things like the Galaxy Gear or the Hexoskin, simply because it was too cumbersome to wear. And I would forget to charge it and the battery life I guess is an issue that I underestimated when I embarked on this study, and how difficult it was to keep track of these devices.
So here’s another kind of typical night of sleep here. So we’ve got 94% sleep efficiency, but the big thing that learned was that the continuous data collection for me seemed to be more valuable than some of these other devices that maybe had more sensors like the Hexoskin. But then there’s this conflict because the Actiwatch doesn’t really produce the data that can detect deep sleep.
So if you kind of look at this graph here, this is produced from the Hexoskin. If you squint your eyes you can kind of see the sleep stages here, but the thing is I mean can this actually be used in a non-invasive way to detect deep sleep basically. And there is scientific evidence, you know Bed-it is a device I’m kind of trying to look into now that can be used to maybe detect deep sleep and this is something that I’m currently exploring. And there’s scientific literature that suggests that the heartrate variability can be used to detect when deep sleep happens.
But really the form factor of the Hexoskin I think didn’t really allow me to explore that very well. And you can see here is when you wear something like the Hexoskin at night you get these bad signals in the data. I mean my heartrate is jumping around here from 50 to 100.
And so I think a really god system for sleep that doesn’t exist yet in order to solve this problem, it needs to have both continuous data and then also good reliable data for heartrate and when that data is unreliable, perhaps it can back up to the continuous tracking data and you can swap out the algorithms like that.
So basically I started out embarking on answering the scientific question, can my deep sleep be enhanced and I kind of stumbled upon these roadblocks in terms of the difficulties in battery life and also just being able to measure things. But now I’m currently trying to figure it out on the Apple watch to see if I can enhance my deep sleep and just improve my sleep just a small amount.
So if you’re interested in this, Daniel Gartenberg.com is my website and you can check out my research on this.