BN5209 Neurosensors and Signal Processing AY13/14

BN5209 Neurosensors and Signal Processing Semester 2, 2013/2014

SCHEDULE

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

  • Tuesday: 5 pm – 7 pm (SINAPSE)
  • Thursday: 5 pm – 7 pm (SINAPSE)

Syllabus

  • Week 1: Mon 13 Jan – Fri 17 Jan
    Introduction to the Course and Introduction to Neurosciences, Neurophysiology
    (Quiz)
  • Week 2: Mon 20 Jan – Fri 24 Jan
    Neural recording methods: Microelectrodes, MEMS, optical neuro sensors
    (Notes) (Quiz)
  • Week 3: Mon 27 Jan – Fri 31 Jan
    Neural recording methods: Neural circuits, amplifiers, telemetry, stimulation
    (Notes)(Quiz 1, Quiz 2)
  • Week 4: Mon 3 Feb – Fri 7 Feb
    Introduction of Signal Processing (Notes)
  • Week 5: Mon 10 Feb – Fri 14 Feb
    Neural signals (basic science) – action potentials (spikes) and analysis
    (Notes)
  • Week 6: Mon 17 Feb – Fri 21 Feb
    Neural signals (clinical applications)- EEG, evoked potentials
    (W6_Part1SpikeDataAnalysis.pdf;W6_Part2ElectrophysiologicalBasisOfNeuralRecordings_Kaiquan.ppt;W6_EEG_EP_NeuralSignalsClinical)
  • Recess Week Sat, 22 Feb 2014 ~ Sun, 2 Mar 2014
  • Week 7: Mon 3 Mar – Fri 7 Mar
    Brain machine interfaces (Notes)
  • Week 8: 10 Mar – Fri 14 Mar
    Multiple Dimensional Signal Processing (Notes) (Quiz)
  • Week 9: Mon 17 Mar – Fri 21 Mar
    Neuroimaging and Neurosurgery (Notes)
  • Week 10: Mon 24 Mar – Fri 28 Mar
    Neurosurgical systems and Microscopic Imaging
  • Week 11: Mon 31 Mar – Fri 4 Apr
    Optical imaging: Cellular (microscopy), In Vivo (speckle, Photoacoustic, OCT)
  • Week 12: Mon 7 Apr – Fri 11 Apr
    Applications of neural interfaces (peripheral and central cortical)
  • Week 13: Mon 14 Apr – Fri 18 Apr
    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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