ramos-ai/MoStress
Implementation of MoStress: a Sequence Model for Stress Classification
This project helps researchers and healthcare professionals automatically identify stress levels from physiological data. By analyzing sensor readings, it can classify whether someone is experiencing stress, providing valuable insights for mental health monitoring or human-computer interaction studies. It is designed for those working with biometric data to understand and categorize human emotional states.
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Use this if you need to analyze physiological sensor data, specifically from chest sensors like those found in the WESAD dataset, to detect and classify stress.
Not ideal if you need an exploratory tool to visualize data or if your dataset is not focused on physiological stress indicators and requires different input types.
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15
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3
Language
Jupyter Notebook
License
MIT
Category
Last pushed
May 16, 2023
Commits (30d)
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