A multi-perceptron neural network that uses EEG and ECG signals to predict stress levels in patients and classify them as having normal, high, and low stress levels.
This model was trained using a 70/30 split, with 70% of data being allocated for training and 30% of data being allocated for testing.
The data used to train this model was sourced from the following source: https://www.kaggle.com/datasets/apithm/ecg-and-eeg-stress-features