BN5209 Neurosensors and Signal Processing AY12/13

BN5209 Neurosensors and Signal Processing Semester 2, 2012/2013

SCHEDULE

Time period: 15-Jan-13 To 10-May-13
Lecture Time:

  • Tuesday: 4:30 pm – 6:30 pm (SINAPSE)
  • Thursday: 4:30 pm – 6:30 pm (SINAPSE)

Syllabus

  • Week 1: Mon 14 Jan – Fri 18 Jan 2013
    Introduction to the Course and Introduction to Neurosciences, Neurophysiology
    (Quiz)
  • Week 2: Mon 21 Jan – Fri 25 Jan 2013
    Neural recording methods: Microelectrodes, MEMS, optical neuro sensors
    (Notes) (Quiz)
  • Week 3: Mon 28 Jan – Fri 1 Feb 2013
    Neural recording methods: Neural circuits, amplifiers, telemetry, stimulation
    (Notes)(Quiz 1, Quiz 2)
  • Week 4: Mon 4 Feb – Fri 8 Feb 2013
    Introduction of Signal Processing (Notes)
  • Week 5: Mon 11 Feb – Fri 15 Feb 2013
    Neural signals (basic science) – action potentials (spikes) and analysis
    (Notes)
  • Week 6: Mon 18 Feb – Fri 22 Feb 2013
    Neural signals (clinical applications)- EEG, evoked potentials
    (W6_Part1SpikeDataAnalysis.pdf;W6_Part2ElectrophysiologicalBasisOfNeuralRecordings_Kaiquan.ppt;W6_EEG_EP_NeuralSignalsClinical)
  • Week 7: Mon 4 Mar – Fri 8 Mar 2013
    Brain machine interfaces (Notes)
  • Week 8: 11 Mar – Fri 15 Mar 2013
    Multiple Dimensional Signal Processing (Notes) (Quiz)
  • Week 9: Mon 18 Mar – Fri 22 Mar 2013
    Neuroimaging and Neurosurgery (Notes)
  • Week 10: Mon 25 Mar – Fri 29 Mar 2013
    Optical imaging: Cellular (microscopy), In Vivo (speckle, Photoacoustic, OCT)
  • Week 11: Mon 1 Apr – Fri 5 Apr 2013
    Neurosurgical systems and Image Processing
  • Week 12: Mon 8 Apr – Fri 12 Apr 2013
    Applications of neural interfaces (peripheral and central cortical)
  • Week 13: Mon 15 Apr – Fri 19 Apr 2013
    Project Reports/presentations

Course Projects

Please log in dropbox to view the materials.
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

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

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

IVLE Registration and Information

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Lectures and Guest Lectures

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