Course topics include quantitative description, analysis, and processing of biological (neural, muscular) signals using computers. Survey of time-frequency representations, correlation, convolution, filtering, and averaging is also included. Some of the topics covered in the course includes introduction to biomedical signals, data acquisition (sampling, reconstruction, ADC, DAC), noise and signal averaging, discrete-time signals and systems, discrete Fourier Transform and FFT, z-Transform, design of FIR and IIR filters, and analysis of neural signals (spikes, EEG, LFPs, ECoG).
Spring of 2019, 2018, 2017, 2016, 2015, 2014, 2013
Neuroengineering and Rehabilitation
This course is designed as an advanced elective course for PhD and MS students. We will cover Neural Engineering theory and applications from the perspectives of electronics design, neural signal analysis, and neurophysiology. Some of the topics covered in the course includes physiology of motor system, abiotic and biotic responses to microelectrode implants, surgical techniques for electrode implantation, neural data acquisition, signal conditioning, PCA and ICA, linear and non-linear decoding of neural signals, coadaptive decoders, design of closed-loop BMI systems, priciples and applications of neurostimulation, and neurorehabilitation.
Fall of 2018, 2017, 2016, 2015
Advances in Neural Engineering have lead to improved medical-device designs with novel functions. This course focuses on the engineering approaches, R&D advances, and technical principles of Neuromotor medical implants.
Fall of 2019, 2014, 2013