/Stress-Prediction-Using-HRV

Using the SWELL dataset from Kaggle, we've built 2 machine learning models to predict whether or not a person is under stress using Heart Rate Variability(HRV) which can be collected from modern wearables such as fitbit devices and apple watches.

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Stress-Prediction-Using-HRV

Using the SWELL dataset from Kaggle, we've built 2 machine learning models to predict whether or not a person is under stress using Heart Rate Variability(HRV) which can be collected from modern wearables such as fitbit devices and apple watches.

Data

https://www.kaggle.com/qiriro/swell-heart-rate-variability-hrv

Models

  • Standard Feed-forward Neural Network: Input Layer(34 neurons, ReLU activation), Hidden Layer(10 neurons, ReLU activation), Output Layer(3 neurons, softmax actionation)
  • KNeighbors Classifer

Applications

The goal is to provide a realtime biofeedback from the wearable when a person undergoes stress. This can be in the form of a notification on the iPhone to prompt the user to use a meditation app, or play a calm song through google home automatically. The data can also be recorded and be displayed using an app.