How to read sleep graphs

If you delete the graph from the Sleep app and it comes back later, check if the graph has icon. Those graphs are synced from external service - either Samsung Health of Google Fit.

If you delete the graphs there too, the they won’t re-appear in the Sleep when you delete them.

​The Sleep Duration is total sum of all your sleep phases (Light, REM, and Deep), not counting the awake phases - because when awake, you are actually not sleeping.
​So on default settings, the Sleep duration is always a bit shorter than the duration of tracking.

​If you wish your Sleep duration is the same as tracking duration:

We use a different input than polysomnographists, and define our own sleep phases, reflecting an objective aspect of sleep, easy to measure with common devices. One naturally needs to ask whether there is any relationship between the EEG-phases and our ACT-phases.

Fortunately, several research teams raised similar questions before (See this one, or this one, or this one, or this one). They measured a bunch of people on a traditional polysomnograph and recorded their physical activity at the same time (By filming them and then counting the movements manually, or by using accelerometer readings). The published analyses show that there indeed is a significant statistical relationship between EEG-phases and body movements.

You can also read about comparison of Sleep as Android algorithms and Sleep lab results on our blog here.

Accelerometric sensors are really sensitive, which is great for sleep tracking. Normally, what you see when you leave the phone on the table gets immediately dwarfed when you do some more significant move. Just leave phone on the table for a while and you will see a dramatic development, but then move the phone and you will see all the development is really tiny in comparison to the new peak.

So what you see is random noise, given by very small vibrations of the table or in very calm areas by seismic movement. We mark the data relatively, so you always get it distinguished into light and deep sleep. But the algorithm works well only in conditions that are assumed by it, i.e. in the bed with relatively large movement peaks.
To be more specific, if you leave the phone on a table, you can get values perhaps on the scale of 0.000001 to 0.000009 m/s2 (The value is made up here, but it is physically very small). In the bed, you may get values from 1 to 9 m/s2 (which is physically large). The algorithm sees though just that the high value is 9 times higher than the low value, in both cases.
We had to do this because every accelerometer (in different cell phones) measures differently, so we couldn’t assume any standard conversion formula that would respond to absolute values.

So if you use the phone in the bed, it is in fact drastically different from measuring on a calm spot, just like the table.

Please do not hesitate to ask for any clarification at support@urbandroid.org. You can also read more about comparison of our data with the sleep lab results in this post.

There can be several reasons why your graphs are flat.

When you can see some movement on the actigraphy, but the graph is unusually flat:
. Sonar - make sure the signal is strong enough by keeping sonar volume at max at Settings → Sleep tracking → Test sensor → blue sliding bar.
- you can also try different frequency by choosing other frequency from the ddrop down menu list in Settings → Sleep tracking → Test sensor → Frequency
- keep the phone closer to you bed
- try different positioning of the phone
. Accelerometer - try keeping the phone closer to you.

If the tracking stops completely after few minutes, the background processes are restricted by your system.

The red block indicates that something went wrong with tracking at that time and the device stopped providing sensor data for some reason. Usually those are some non-standard battery optimizations or battery savers, the battery gets too low so we preserve it for the alarm or connectivity issue if you use a wearable.