refine readme

Android/README.md

@@ -39,7 +39,7 @@ Data Encryption is not part of this app, but it can easily be integrated (as des
 You may also change `signup_password` (default: 'start'), the password required when starting the application.
 
 
-###SharedPrefs
+### SharedPrefs
 Mynd keeps track of some data like the study state and the user name on the device in 
 SharedPreferences, whenever the app is not in use. In the `SharedPrefsController`, you can change the version name of the app, in case
 breaking changes to the storage model are introduced.

README.md

@@ -9,12 +9,12 @@ Using thoughts to interact with our surroundings through brain-computer interfac
 ## Versions
 Scientific supervision of this project was provided by Prof. Dr. Moritz Grosse-Wentrup, University of Vienna, and Prof. Dr. Bernhard Schölkopf, Max Planck Institute for Intelligent Systems.
 
-### iOS
+### [iOS](./iOS)
 This version was developed by Matthias Hohmann as part of a research project on large-scale neuroscientific experiments at the Max Planck Institute for Intelligent Systems, Tübingen, Germany. Assistance was provided by Raffi Enficiaud, Talha Zaman, Michelle Hackl and Brian Wirth. 
 
 This version features 1) the ability to connect to a consumer-grade EEG (currently the Muse EEG headband), 2) fit the headset by using a real-time feedback algorithm on signal quality, 3) record questionnaire or neurophysiological data in multi-day studies, with a flexible timeout mechanism, 4) transfer the data to a server with asymmetric encryption, 5) data storage in widely-used HDF5 and JSON formats, 6) abstracted signal processing through observer-patterns, 7) localization. Documentation and starting points to assist with likely future developments are presented in [docs](./iOS/docs/index.md).
 
-### Android
+### [Android](./Android)
 This version was developed by Brian Wirth as part of a summer internship at the Max Planck Institute for Intelligent Systems, Tübingen, Germany. Assistance was provided by Michelle Hackl and Matthias Hohmann. 
 
 This version features 1) the ability to connect to a consumer-grade EEG (currently the Muse EEG headband), 2) fit the headset by using a real-time feedback algorithm on signal quality, 3) record neurophysiological data, 4) transfer the data to a server, 5) data storage in widely-used CSV, 6) abstracted signal processing through observer-patterns.
@@ -24,9 +24,6 @@ This version was developed by Talha Zaman and Raffi Enficiaud as part of their w
 
 *TBA*
 
-## Cite this framework
-*tbd*, e.g. Matthias R. Hohmann, Brian Wirth, Michelle Hackl, Talha Zaman, Raffi Enficiaud, Moritz Grosse-Wentrup, and Bernhard Schölkopf. (2020). MYND: Neuroscience at Home. Zenodo. http://doi.org/XX.XXX/zenodo.XXXXXXX
-
 ## Scientific Publications using MYND
 1. Hohmann, M. R., Konieczny, L., Hackl, M., Wirth, B., Zaman, T., Enficiaud, R., Grosse-Wentrup, M., & Schölkopf, B. (2020). MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware. http://arxiv.org/abs/2002.11754
 
@@ -35,7 +32,8 @@ This version was developed by Talha Zaman and Raffi Enficiaud as part of their w
 3. Hohmann, M., Hackl, M., Wirth, B., Zaman, T., Enficiaud, R., Grosse-Wentrup, M., & Schölkopf, B. (2019). Forschung mit allen: Eine Smartphone App zur Teilnahme an neurowissenschaftlicher Grundlagenforschung in ALS. Nervenheilkunde, 38(05), P22. https://doi.org/10.1055/s-0039-1685040
 
 ## License
-Details about the license of this project can be found [here](./LICENSE.md)
+Details about the license of this project can be found [here](./LICENSE.md). For other
+licensing options please contact Max-Planck-Innovation ([email protected]) with the reference `MI 0104-5982-BC-JK`.
 
 ## Documentation
 Please have a look at the individual README files of each sub-project for more information.