BiosEmo - An Interest Project: Emotion Classification based on Biosignal data

Demo

• en-US Video
• zh-TW Video

Preparation

1. Install Python 3
2. Install Jupyter: pip install jupyterlab
3. Install Python packages: Run with python3 notebooks/deploy.py (Should crash in the first time because newly installed packages may not be cached immediately)
4. Set OPENAI_API_KEY as an environment variable
5. Install bun (A fast all-in-one JavaScript runtime)

Deployment

Run with python3 notebooks/deploy.py and open the web app in your browser. Link: http://localhost:8080

You can find some test data for Web app at ./datasets/swell/final/web-SIT/. Upload them via GUI and have fun!

Reproduce the experiments

Open your Jupyter environment and run them in this order:

1. notebooks/preprocess.ipynb
2. notebooks/analyze.ipynb

Web app development

Run with bun run dev or bun run build.

The URL is http://localhost:8081

Note: It is OK to run development and production server at the same time. Big thanks to Vue's .env file.

Documentations

• Algorithms: link | 連結
• Frameworks: link | 連結
• Dataflow: link | 連結
• Workspace: link | 連結

Datasets

SWELL (Kaggle)

This dataset comprises of heart rate variability (HRV) indices computed from the multimodal SWELL knowledge work (SWELL-KW) dataset for research on stress and user modeling (see. http://cs.ru.nl/~skoldijk/SWELL-KW/Dataset.html).

• sources:
  • link 1
  • link 2
  • link 3
  • link 4
• citations

1. S. Koldijk, M. A. Neerincx, and W. Kraaij, “Detecting Work Stress in Offices by Combining Unobtrusive Sensors,” IEEE Trans. Affect. Comput., vol. 9, no. 2, pp. 227–239, 2018.
2. S. Koldijk, M. Sappelli, S. Verberne, M. A. Neerincx, and W. Kraaij, “The SWELL Knowledge Work Dataset for Stress and User Modeling Research,” Proc. 16th Int. Conf. Multimodal Interact. - ICMI ’14, pp. 291–298, 2014.
3. Kraaij, Prof.dr.ir. W. (Radboud University & TNO); Koldijk, MSc. S. (TNO & Radboud University); Sappelli, MSc M. (TNO & Radboud University) (2014): The SWELL Knowledge Work Dataset for Stress and User Modeling Research. DANS. https://doi.org/10.17026/dans-x55-69zp

Other References

Heart Rate Variability Metrics and Norms

• source: link