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gesture-interaction-wristband

This project focuses on recognizing hand gestures and interacting through them with a dashboard. We use the Tunderboard React by Silicon Labs.

We created a uitility to record gestures in /recorder. These recoded data sets are used to train the machine learning algorithm. We chose a Voting classifier with RandomForest and 5-Neighbors as provided by the scikit-learn packages. Dashboard and gesture recognition are implemented in /recognition. Interfacing the Thunderboard React happens through a NodeJS script. For more details on system architecture please refer to /paper where we described the project and its outcome.

Installation

Installation on Mac OS:

  1. Make sure Xcode, NodeJS and Anaconda (Python 2.7) are installed
  2. Go to /connector, run npm install
  3. Run pip install numpy scikit-learn pydot pandas matplotlib

Usage

To launch the recording cd into /connector and execute

node gesture.js ../recorder/app.py

To launch the recognition along with the dashboard cd into /connector and execute

node gesture.js ../recognition/app.py

Note that this project was built upon Python 2.7 and relies on Anaconda.