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What is Sleep Stage and Heat Stress Classification about?

This chapter discusses using a radial basis function neural network for classifying sleep stages and stress conditions from EEG data. It is divided into two parts: classifying sleep stages into awake, slow wave sleep, and REM sleep with an accuracy of 87.25%, and classifying heat stress conditions into acute and chronic with 90.5% accuracy. Features like band power from EEG signals and EMG/EOG activity are extracted and used as inputs to the neural network, which is trained and tested on labeled data sets f

Author

Swapnil Jha

Language

EN