BN5209 Neurosensors and Signal Processing AY14/15

BN5209 Neurosensors and Signal Processing Semester 2, 2014/2015

SCHEDULE

Time period: 14-Jan-14 To 9-May-14
Lecture Time:

  • Tuesday: 5 pm – 7 pm (E3-06-04)
  • Friday: 5 pm – 7 pm (EA-06-03)

Instructors

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

Syllabus

  • Week 1: Jan 13,16
    Intro to the Course (NT,HR)
    Intro to Neurosciences (NT)
  • Week 2: Jan 20,23
    Neural recording methods: Microelectrodes, MEMS, optical neuro sensors (NT)
  • Week 3: Jan 27,30
    Neural recording methods: Neural circuits, amplifiers, telemetry, stimulation (NT)
  • Week 4: Feb 3,6
    Introduction of BioSignal Processing (HR)
  • Week 5: Feb 10,13
    Prepare Student Seminars – paper selection
    Time-Frequency-Spatial Analysis STFT (HR)
  • Week 6: Feb 17, 20(holiday)
    Neural signals (clinical applications)- EEG, evoked potentials (HR)
    Lab tutorial for Project I: Neural Signals and Analysis
  • Recess Week Sat, 22 Feb 2014 ~ Sun, 2 Mar 2014
  • Week 7: Mar 3,6
    Multiple Dimensional Signal Processing (HR)
    Lab Project II: Application in neural systems
  • Week 8: Mar 10,13 (eLearning)
    Student Reading Seminars 5209 (HR)
    Student Reading Seminars 6209 (NT,HR)
  • Week 9: Mar 17,20
    Brain machine interfaces (NT)
    EEG/ECoG
  • Week 10: Mar 24,27
    BMI- Neural Spikes (NT)
    Optical imaging: Cellular (microscopy), In Vivo (Speckle, Photoacoustic, OCT) (NT)
  • Week 11: Mar 31, Apr 3
    Neuroimaging and Image Processing (HR)
    Neuroimaging fMRI (HR)
  • Week 12: Apr 7,10
    Advanced Neurosignal Processing / Neurosurgical systems (HR)
    Applications of neural signal processing (HR)
  • Week 13: Apr 14,17
    Project Reports (due before final)/presentations (HR, NT)

Course Projects

1. EEG for brain state monitoring
2. EEG/EMG Feature Identification during Elbow Flexion/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 (2 for 20%)
Seminars (1 for 10%)
Take Home Final Exam(20% )

 

IVLE Registration and Information

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