BN5209-6209 Neurosensors and Signal Processing/Neurotechnology AY15/16

BN5209/BN6209 Neurosensors and Signal Processing / Neurotechnology Semester 2, 2015/2016

SCHEDULE

Lecture Time:

  • Tuesday: 3 pm – 6 pm (EA-06-03)

Instructors

  • Professor Nitish THAKOR (NT)
  • Assistant Professor Hongliang REN (HR)
  • Invited lecturers

Syllabus

Note: Information contained in this syllabus may be subject to change.

Week Topic
1

Jan12

Intro to the Course (NT)

Intro to Neurotechnology  (NT)

2

Jan19

Introduction of BioSignal Processing  (HR)

L1-CFT; L2-Stochastic Process/R.V./Moments/PSD

3

Jan26

Neural recording methods: Neural circuits, amplifiers, telemetry, stimulation (NT)
4

Feb2

Prepare Student Seminarspaper selection

Time-Frequency-Spatial Analysis  STFT (HR)

5

Feb9 (CNY)

Holidays
6

Feb16

Neural signals (clinical applications)- EEG, evoked potentials (HR)

Lab tutorial for Project I: Neural Signals and Analysis

Recess Feb22
7

Mar1

Multiple Dimensional  Signal Processing (HR)

Lab Project II: Application in neural systems

Student Reading Seminars (HR)

8

Mar8

Neuro Diagnostic and Therapeutic Devices by NT
9

Mar15

Brain machine interfaces  (NT)

EEG/ECoG

10

Mar22

Neuromorphic Engineering – Brain Inspired Robotics by SK
11

Mar29

Neuroimaging and Image Processing (HR)

Neuroimaging fMRI (HR)

12

Apr5

Advanced Neurosignal Processing / Neurosurgical systems (HR)
13

Apr12 (makeup)

Project Reports (due before final) & presentations (HR, NT)

Course Projects

1. EEG for brain state monitoring
2. EEG/EMG Feature Identification Extension

AIMS & OBJECTIVES

This module teaches students the advanced neuroengineering principles ranging from basic neuroscience introduction to neurosensing technology as well as advanced signal processing techniques. Major topics include: introduction to neurosciences, neural recording methods, neural circuits, amplifiers, telemetry, stimulation, sensors for measuring the electric field and magnetic field of the brain in relation to brain activities, digitization of brain activities, neural signal processing, brain machine interfaces, neurosurgical systems and applications of neural interfaces. The module is designed for students at Master and PhD levels in Engineering, Science and Medicine.

PREREQUISITES

Basic probability
Basic circuits
Linear algebra (matrix/vector)
Matlab or other programming
Recommended Textbooks: Neural Engineering, Edited by Bin He
Seminar papers

TEACHING MODES

The majority of the course will be in lecture-tutorial format. Some advanced topics will be in the formats of seminar and research presentations.

ASSESSMENT

Take Home Tests (5 for 50%)
Labs/Projects Reports + Presentations (20%)
Seminars (10%)
Take Home Final Exam(20%)

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