I average 4 dreams a night – what’s the shape of your sleep?

Every night, we surrender ourselves to the most enigmatic aspects of our reality – sleep. We voluntarily (or involuntarily) enter this dormant state of being for 1/3rd of our life, each time waking up hours later to face the remaining 2/3rd of of the day.

What exactly happens when we are unconscious? You can always go to a sleep lab and have all sorts of machines monitoring your brain frequencies and other vitals so that you can learn more about how you sleep. But if you want the convenience of doing it yourself, you can try this $0.99 app for the iPhone called Sleep Cycle.

The setup

You start Sleep Cycle, leave it running, and place the iPhone face down on the mattress, somewhere near your head area. SleepCycle uses the accelerometer in an iPhone to detect motion as you sleep. This motion is interpreted as a proxy for how active your brain is at that time. When you wake up the next day, you can see a graph of your sleep activity the past night.

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Certain levels of activity are associated with different stages of sleep. Lowest activity corresponds to deep slumber when we have no dreams. Some activity corresponds to the stage of Rapid Eye Movement when we have all of our dreams. And high activity corresponds to light sleep – the kind that leaves you tired when you wake up.

Sleep graphs

I have been monitoring my sleep this way for a couple of months now. I have noticed that on average I seem to have 4 instances of REM like activity levels. Does that mean I have as many distinct dreams each night? Most research points out that this is in fact close to the average number of dreams humans have. However, I rarely remember my dreams; so this is insightful for me to understand that my brain is being creative while I am unconscious 🙂

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And then there are some days where I have interesting variations. For example, the two graphs below are quit extreme when compared to each other. According to the first one I plunged straight into deep sleep as soon as I lied down. But within an hour I was almost awake. I stayed in the high activity area dipping twice to catch 2-3 quick dreams but was pretty much sleeping lightly for the rest of the night. I am guessing it’s one of those nights when your dreams take input from what’s actually happening outside and distorts it into a fantasy dream world experience. Unfortunately, I don’t remember what I dreamt that night so I have no way of validating this.

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The one on the right, however, suggests that I stayed in deep sleep for most of the night. I only had a dream around 5:00 am before going back to deep sleep. Is this one of the nights where I actually remember what I dreamt since there was only one? I am not sure because I really couldn’t remember what I dreamt.

Waking up at the “right” time

If you look closely at all the graphs there is one thing in common to almost all of them. They all end on an uptick in my sleep graph – did you notice that? This is no co-incidence. This is the second feature in this app which makes it an awesome alarm clock. You set the time you want to wake up and then use the app as described earlier. Around 30 minutes before your wake up time the app starts looking for increase in activity. As soon as it notices your body’s activity level going up, it triggers the alarm even if it’s 10s of minutes before your desired wake up time. The theory is that if you are woken up at a time when your body is naturally trending towards being active then you wake up feeling more active and less groggy.


I am not sure I can say for certain that this helped me – it’s really hard to notice difference in grogginess – and I am never super happy to wake up 🙂 And that’s the other problem with the app – there’s no snooze button. So if I don’t want to wake up, I have to quit the app to shut the alarm. Then it stops recording consequent activity, though, so the graphs are not true to the actual time you wake up in case you snoozed.

Augmented mindfulness

At SXSW this year, Robert Fabricant of Frogg Design described Augmented Mindfulness. It’s the idea of collecting information about yourself, processing it, reporting it and then reflecting on it to effect change in yourself.

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Sleep Cycle is a great app for the curious and I highly recommend trying it out. However, this data can’t be exported, nor can it be analyzed or visualized in other ways. So it’s limited in how much it can help you in making deeper insights into yourself. It would be great if I could correlate this data with other data about me. For example, I could look at my tweets or social updates of the preceding day to analyze my sentiment and derive my mood and then find correlations with my sleep patterns and how I was feeling that day. Or I could compare it with the food I ate that day that I capture in my food journal.

My Fitbit finally got delivered today. It also lets you monitor your sleep and helps you reflect on your data. It will be interesting to compare how the data differs across the two systems. I will find out soon!



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