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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Lectures and Guest Lectures
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