https://github.com/andreibarsan/oxford-hack-16

https://github.com/andreibarsan/oxford-hack-16

Last synced: 20 days ago
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• Host: GitHub
• URL: https://github.com/andreibarsan/oxford-hack-16
• Owner: AndreiBarsan
• Created: 2016-11-20T00:47:08.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2016-11-23T12:24:14.000Z (about 8 years ago)
• Last Synced: 2024-04-10T02:16:09.642Z (9 months ago)
• Language: Jupyter Notebook
• Size: 75.7 MB
• Stars: 2
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# OxfordHack 2016 Project: Computer Control using the Muse Headband

Team: **we use muse**

Members: Andrei Barsan, Andrej Hoos, Pavel Kalvoda

For this project, we experimented leveraging the Muse Headband, which tracks

a user's brain activity using real-time EEG measurements.

We performed a statistical analysis of different activities (relaxing,

listening to music, versus being actively focused on a task such as text

editing). We built a visualization dashboard to track a user's focus, but the

classifier still needs more tuning before being useful in practice.

In a separate application, we also leveraged the device's accelerometer to

allow users to interact with the computer using head movements (by translating

head movements to mouse movements). This currently

works quite well. The code for this application resides in the `mouse/`

directory, and only supports OS X at the moment.

The raw data should be saved in the `recordings/` folder (child of the project

root). The data we collected at the hackathon is contained in the

`recordings.7z`, which is a 7zip archive. Its quality is not great, since the

recordings were performed in a relatively noisy and distracting environment,

but there is *some* signal in them. The 'baseline' recordings involve random

internet browsing. The 'relax' and 'relaxed' ones, attempts at meditation.

'forward', 'left', 'right' involve focusing on moving in that direction (they

don't seem to carry much relevant signal). 'helicopter' involves focusing on

thinking about a helicopter. As you can probably imagine, there is basically no

signal in this particular case, since the device has quite limited accuracy.

The 'typingtest' files are recordings of me focusing on a typing speed test,

while listening to music.

Please use `muse2csv.sh` to convert the raw data to `csv`, which can then be

imported in the `pymuse/nb/EEG-Analysis.ipynb` Jupyter notebook for analysis.