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It is possible to revert up to 5 changes made while editing a graph.

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

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

Sleep duration is the sum of all your sleep stages (light, REM, and deep), not including waking stages - because you are not really sleeping when you are awake.
So on default settings, your Sleep Duration ,ay be a little shorter than your tracking time.

If you want your sleep duration to be the same as your 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.

Accelerometers are really sensitive, which is great for sleep tracking. Usually what you see when you leave the phone on the table is immediately dwarfed when you make a more significant movement. Just leave the phone on the table for a while and you will see a dramatic spike, but then move the phone and you will see that all the development is really tiny compared to the new peak.

So what you see is random noise caused by very small vibrations of the table or in very quiet areas by seismic movement. We mark the data relatively, so you can always distinguish between light and deep sleep. However, the algorithm works well only in conditions, it assumes i.e. in the bed with relatively large movement peaks.
To be more precise, if you leave the phone on a table, you may get values perhaps in the range of 0.000001 to 0.000009 m/s2 (the value is made up here, but it is physically very small). In the bed, you can get values from 1 to 9 m/s2 (which is physically large). However, the algorithm only sees that the high value is 9 times higher than the low value in both cases.
We had to do this because each accelerometer (in different phones) measures differently, so we couldn’t assume a standard conversion formula that responds to absolute values.

So if you use the phone in bed, it is indeed drastically different from measuring in a quiet place, like the table.

Please do not hesitate to contact support@urbandroid.org for clarification. You can also read more about how our data compares to sleep lab results at in this post.

There are several reasons why your graphs may be flat.

If you can see some movement on the actigraphy, but the graph is unusually flat:
. Sonar - make sure the signal is strong enough by keeping the sonar volume at max at Settings → Sleep tracking → Test sensor → blue sliding bar.
- You can also try a different frequency by selecting other frequency from the drop-down menu list in Settings → Sleep tracking → Test sensor → Frequency
- Keep the phone closer to your bed.
- Try different positions 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.