MATLAB Course

Session1: Introduction to Research areas in Biomedical Engineering | Popular Dataset | Signal | Image

Session2: Pattern Recognition

■ what is pattern recognition? | Types of Machine learning | Feature Extraction | Divide Data for Train and Test | K-fold Cross Validation | Leave-one-out | R-Method | H-Method

Session3: Introduction to MATLAB programming

Session4: for,while loop | if statements | switch-case | write functions

Session5,6: Introduction to Biomedical Image processing,

■ Grayscale and Color Images | Contrast Adjustment | Segmentation | Thresholding Intensity Values | Binary Images

Pre- and Postprocessing techniques | Classification and Batch Processing

Projects: Breast Cancer project | Diabetic Retinopathy | Retinal Blood Extraction

Session7,8: Introduction to Biomedical Signal processing

■ Fast Fourier Transform | Short-time Fourier Transform | Wavelet

Projects: EEG Bonn Dataset | BCI Motor Imagery | ECG Processing

Session9,10: Classifiers

■ KNN | SVM | DTree | LDA | Naive Bayesian

Projects: EEG Bonn Dataset | BCI Motor Imagery

Session11: Feature Selection

■ Filter Method: T-test and Anova | Wrapper: Sequential Forward Feature Selection

Projects: EEG Bonn Dataset | BCI Motor Imagery

Session12: Band Selection, Channel Selection

Projects: EEG Bonn Dataset | BCI Motor Imagery

Session13: Introduction to Deep Learning