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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