Digital Signal Processing
An introduction to the concept of continuous and discrete signals and systems. Difference equations, Discrete Fourier Transforms (DFTs), Fast Fourier Transforms (FFTs), Z-Transform techniques, Filter analysis are covered. An introduction to the bio medical signal processing using MATLAB/ any programming language.
This course rigorously and clearly explains the latest developments and basic engineering principles of the entire spectrum of biomedical devices-ranging from their physiological basis to diagnostic and therapeutic devices in medical imaging systems.
Neural Signal Processing
Neural signal processing is aimed to extract information from neural signals for the purpose of understanding how the brain represents and transmits information through neuronal ensembles. In this course, brain physiology is covered with special emphasis on the functions of different parts of the brain and the different types of electrical impulses generated from these parts. Working principle of Electroencephalography (EEG) is covered in detail with live EEG demonstration.
This course is a study of feedback control systems theory including practical applications of compensation and PID concepts. Control system modeling, transient and steady state characteristics, stability and frequency response are analyzed. Compensation and controller design using Root locus methods are covered. The use of control system software, such as MATLAB, in the analysis and design of control systems is emphasized.
Using Deep Learning to Identify Multilingual Music Genres
Spectrogram of a French Hip-Hop Song
Effect of Blue Light on Sleep Pattern
Fourier Transform of brain signals with blue light exposure
Brain Computer Interface Study on Patients with Central Nervous System Injury
Optimized electrode positions for BCI study for CNS injured patients
Brain Computer Interfacing RC Car
An image of Raspberry Pi interfacing Transmitter