Sleep Classification with Python | EEG, Sklearn and MNE | Part 1

[@Mohamm-ed]

Awesome video thanks

[@deeplearningexplained]

I’m glad it’s useful!

[@siddharthvj1]

In this data, there should be seasonality because a person generally sleeps at the same time every day. After this, we can use seasonal decomposition and then apply the SARIMA model.

[@deeplearningexplained]

Interesting thought, what do you mean by seasonality though? Like time of day?

[@siddharthvj1]

@@deeplearningexplained Yes, I mean that seasonality refers to the regular, predictable patterns in the data that repeat over a specific period. In this case, it could be daily sleep patterns, where a person tends to sleep at the same time every night. By identifying these seasonal patterns, we can better understand the data and apply seasonal decomposition techniques before using the SARIMA model for more accurate forecasting.

[@deeplearningexplained]

⁠@@siddharthvj1ah right yes that would be awesome to have that circadian pattern information per participant!
This study was conducted in a sleep lab though with heavy wiring of equipements so it might skew a bit the normal sleep pattern.
There are two recorded night per participant I’ll check if the sleep stage pattern per participant match in another video!