BN5209
NEUROSENSORS AND SIGNAL PROCESSING (2012/2013, Semester 2) 

 MODULE OUTLINE Created: 21-Dec-2012, Updated: 21-Dec-2012
 
Module Code BN5209
Module Title NEUROSENSORS AND SIGNAL PROCESSING
Semester Semester 2, 2012/2013
Modular Credits 4
Faculty Engineering
Department Biomedical Engineering
Timetable Timetable/Teaching Staff
Module Facilitators
DR Ren Hongliang Lecturer
PROF Thakor, Nitish Vyomesh Lecturer
DR Ignacio Delgado Martinez Research Fellow
Weblinks
Tags --


Learning Outcomes | Prerequisites | Teaching Modes | Schedule | Synopsis | Syllabus | Assessment | Workload


 LEARNING OUTCOMES Top
This module teaches students the advanced neuroengineering principles ranging from basic neuroscience introduction to neurosensing technology as well as advanced signal processing techniques.  electrical and magnetic field of the human brain in relation to the brain activities and methods for sensing the electrical and magnetic field of human brain in relation to brain activities. 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 Top
•Excitement
•Basic probability
•Basic circuits
•Linear algebra (matrix/vector)
•Matlab or other programming


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


 SCHEDULE Top
1 Intro to the Course
Intro to Neurosciences
2 Neural recording methods: Microelectrodes, MEMS, optical neuro sensors
3 Neural recording methods: Neural circuits, amplifiers, telemetry, stimulation 
4 Introduction of BioSignal Processing
5 Neural signals (basic science) - action potentials (spikes) and analysis
6 Neural signals (clinical applications)- EEG, evoked potentials
Lab Project I: Neural Signals and Analysis

7 Brain machine interface
8 Multiple Dimensional  Signal Processing
9 Neuroimaging and Image Processing
10 Optical imaging: Cellular (microscopy), In Vivo (speckle, Photoacoustic, OCT) 
11 Neurosurgery  / Neurosurgical systems
Lab Project II
12 Applications of neural interfaces
Lab Project III
13 Project Reports/presentations



 SYNOPSIS Top
  The course will start with basic neuroscience principles and followed Neuro-engineering Fundamentals in order to give students a big picture on the subjects. We will focus on Neuro Sensors & Signal Processing to address the neuroengineering problems and will cover the state of the arts in the area and relevant topics.


 SYLLABUS Top
Intro to Neurosciences
Neural recording methods: Microelectrodes, MEMS, optical neuro sensors, Neural circuits, amplifiers, telemetry, stimulation 
BioSignal Processing
Neural signals (basic science) - action potentials (spikes) and analysis
Neural signals (clinical applications)- EEG, evoked potentials
Brain machine interface
Multiple Dimensional  Signal Processing
Neuroimaging and Image Processing [including advanced Optical imaging: Cellular (microscopy), In Vivo (speckle, Photoacoustic, OCT)]
Neurosurgical systems
Applications
Lab Projects


 ASSESSMENT Top
–In Class Quizzes (10 for 20% grade)
–Take Home Tests (2 for 50% or Exam)
- Labs/Projects (3 for 30%)


 WORKLOAD Top
3-0-1-1-2

Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week