Machine LearningCoursework
Sleep Stage Classification
Multimodal EEG, EOG, EMG sleep staging in MATLAB
About
KTH project for automatic sleep staging from polysomnography. Three phases: EEG-only, EEG+EOG, EEG+EMG+EOG. Modular preprocessing (notch, high-pass, low-pass) with toggles, 30-second epoch segmentation, and time, frequency, and wavelet feature extraction including spectral entropy and eye-movement features. Grid-searched k-NN, RF, MLP, and SVM classifiers across single-modality and multimodal pipelines, with caching for filtered signals and features. Confusion matrices and PCA visualizations exported to Excel and LaTeX.
Status
Submitted for the KTH biosignal processing course.
Stack
MATLABEDFWaveletsSVMSignal Processing