# MiSleep
MiSleep is for EEG/EMG signal processing and visualization
## Get start
```shell
pip install misleep==0.1.1
```
Find the directory where you installed misleep, run
```shell
python -m misleep
```
### New features
1. New data structure
You can save the original data as a new data structure (See `Data save protocol`).
Where you can add the channels' name, sampling rate and the acquisition time into
the original data.
2. Annotate more details
Here we provide the start_end mode as a more precise way to annotate the event such
as Slow Wave Activities or Spindle, e.t. You can select the `Start-End` mode in
the Annotation tool dock and click wherever in the signal area to annotate the
event.
2. Tool bar dock
Now you can move the toolbar to wherever you want.
3. Color for state
Different color background for different sleep states. Now the color map is:
Init: White; NREM: Orange; REM: Blue; Wake: Red.
**Future**: you can self-define the color for each sleep state.
## Data save protocol
You need to use matlab for data saving, the final data should be a structure.
If you are using TDT for recording, here is the example script to save the data.
```matlab
tdt_data = ...
data.EEG_F = tdt_data.streams.EEG1.data(1, :);
data.EEG_P = tdt_data.streams.EEG1.data(2, :);
data.EEG_DIFF = data.EEG_F - data.EEG_P
data.EMG_1 = tdt_data.streams.EMG1.data(1, :);
data.EMG_2 = tdt_data.streams.EMG1.data(2, :);
data.EMG_DIFF = data.EMG_1 - data.EMG_2;
data.REF = data.streams.mou1.data(1, :);
data.channels = {'EEG_F' 'EEG_P' 'EEG_DIFF' 'EMG_1' 'EMG_2' 'EMG_DIFF' 'REF'}
data.sf = {305.1758 305.1758 305.1758 305.1758 305.1758 305.1758 305.1758}
data.time = {'20240409-18:00:00'}
```
And an example of result data:
Raw data
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"description": "# MiSleep\r\nMiSleep is for EEG/EMG signal processing and visualization\r\n\r\n\r\n\r\n## Get start\r\n```shell\r\npip install misleep==0.1.1\r\n```\r\n\r\nFind the directory where you installed misleep, run\r\n```shell\r\npython -m misleep\r\n```\r\n\r\n### New features\r\n1. New data structure\r\n\r\nYou can save the original data as a new data structure (See `Data save protocol`).\r\nWhere you can add the channels' name, sampling rate and the acquisition time into \r\nthe original data.\r\n\r\n2. Annotate more details\r\n\r\nHere we provide the start_end mode as a more precise way to annotate the event such\r\nas Slow Wave Activities or Spindle, e.t. You can select the `Start-End` mode in\r\nthe Annotation tool dock and click wherever in the signal area to annotate the \r\nevent.\r\n\r\n2. Tool bar dock\r\n\r\n\r\n\r\nNow you can move the toolbar to wherever you want.\r\n\r\n3. Color for state\r\n\r\n\r\n\r\nDifferent color background for different sleep states. Now the color map is:\r\n\r\nInit: White; NREM: Orange; REM: Blue; Wake: Red.\r\n\r\n**Future**: you can self-define the color for each sleep state.\r\n\r\n\r\n\r\n## Data save protocol\r\nYou need to use matlab for data saving, the final data should be a structure.\r\n\r\n\r\nIf you are using TDT for recording, here is the example script to save the data.\r\n```matlab\r\ntdt_data = ...\r\n\r\ndata.EEG_F = tdt_data.streams.EEG1.data(1, :);\r\ndata.EEG_P = tdt_data.streams.EEG1.data(2, :);\r\ndata.EEG_DIFF = data.EEG_F - data.EEG_P\r\ndata.EMG_1 = tdt_data.streams.EMG1.data(1, :);\r\ndata.EMG_2 = tdt_data.streams.EMG1.data(2, :);\r\ndata.EMG_DIFF = data.EMG_1 - data.EMG_2;\r\ndata.REF = data.streams.mou1.data(1, :);\r\ndata.channels = {'EEG_F' 'EEG_P' 'EEG_DIFF' 'EMG_1' 'EMG_2' 'EMG_DIFF' 'REF'}\r\ndata.sf = {305.1758 305.1758 305.1758 305.1758 305.1758 305.1758 305.1758}\r\ndata.time = {'20240409-18:00:00'}\r\n```\r\nAnd an example of result data:\r\n\r\n\r\n",
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