WhiteICE documentation
======================

WhiteICE plays sounds (+ possible visuals) in the background to increase concentration or an other EEG target set by user.
WhiteICE requires EEG-device to use and keeps optimizing stimulus while audio(visual) stimulation is done.
WhiteICE supports two EEG devices: BrainAccess HALO EEG (through LSL protocol) and Interaxon Muse EEG (through MindMonitor OSC output).

To play sounds in the background with LSL or OSC protocol use commands

./whiteice --measure --device=lsl --concentration (BrainAccess HALO EEG)
./whiteice --measure --device=mindmonitor --concentration (Interaxon Muse EEG and MindMonitor App with target UDP port 4545).

If you want just test the software you can also use random device

./whiteice --measure --device=random --concentration

Software runs about 30 minutes when started in measurement mode where measurements of random stimulus is measured without
optimizing stimulus model after 30 minutes machine learning models are computed using reinforcement learning to find
stimulation that minimizes distance to target state. Besides concentration you can also set "--sleep" or "--relax" targets.
You can also set other targets with "--target=0,1,0,1,0,..." switch (values should be 0 or 1 or -1 if that signal's target is not set).

You can typically get about 0.5% effect towards target values.

WhiteICE should be used to measure EEG and play sounds in the background while using computer. Typically for good results
deep reinforcement algorithms should be run 1-2 hours or longer.

If you have multiple LSL devices in the local network, you can select certain LSL stream "--lsl-names='device name','EEG typename'".

If LSL device has more than 4 channels, you can set. --lsl-channels=8 to use 8-channel EEG. Currently software algoritms scale
as O(N^2) where N is number of EEG-channels so number of EEG channels cannot be very large (16 channels is means already
quite much computation in the background requiring fast CPU).

LICENSE
=======

This software is closed source but free to use (freeware).
Links with non-GPL libraries.

Software should be useful but machine learning algorithms only work statistically and may not work.
Software creator isn't responsible for any damage use of this software may cause
(thought audiovisual stimulation is quite safe in practice).


Softare is developed by Tomas Ukkonen (tomas.ukkonen@iki.fi)

