1. Make sure your device has a python API
2. Connect your device with python
3. Call your device through CogBeacon's main.py (see lines 527-538)
4. Write your one function that binds your device the the appropriate variables captured by CogBeacon (similarly to how it is done in function readMuse(), readFrames() and SelfReport() in main.py)

1. Kivy Python Cross-Platform Gui library 1.9.0 or newer

Install Muse tools: http://dev.choosemuse.com/tools Install Python SDK Tools: http://das.nasophon.de/pyliblo/ Note: since we use 64-bit Linux OS, check the following link for MuseSDK on 64-bit system: http://forum.choosemuse.com/t/issues-running-muselab-and-muse-io/112/20 or https://github.com/elnn/tomato/blob/master/README.md

For additional help please contact the author at: michalis.papakostas@mavs.uta.edu or mpapakos@umich.edu

More instructions along with detailed documentation will be added soon.

Papakostas, Michalis, Akilesh Rajavenkatanarayanan, and Fillia Makedon. "CogBeacon: A Multi-Modal Dataset and Data-Collection Platform for Modeling Cognitive Fatigue." Technologies 7.2 (2019): 46.

@article{papakostas2019cogbeacon, title={CogBeacon: A Multi-Modal Dataset and Data-Collection Platform for Modeling Cognitive Fatigue}, author={Papakostas, Michalis and Rajavenkatanarayanan, Akilesh and Makedon, Fillia}, journal={Technologies}, volume={7}, number={2}, pages={46}, year={2019}, publisher={Multidisciplinary Digital Publishing Institute} }