Classroom_stress

Evaluate stress level through resting EEG

Build environment

Install Anaconda and build a virtual environment by following codes

conda create -n classroom python=3.7
conda activate classroom
pip install -r requirements.txt

Input new data

Since I hard-coded different forms to read data according to the folder name, it would be easier to change the folder name to resting_ASR with ch_lib.mat in this folder and put them in data/.

Run evaluation

• Open classification.ipynb
• Modify parameters (choose input_type, frequency range, select models...)
• Run evaluation, csv files containing results for each combination of methods will be generated automatically in results/{folder}/
• Find highest performance among multiple csv files, modify data_name to be the above {folder}, highest performance for different validation methods will be recorded in results/record.csv