BN5209-6209 Neurosensors and Signal Processing/Neurotechnology AY15/16

BN5209/BN6209 Neurosensors and Signal Processing / Neurotechnology Semester 2, 2015/2016

SCHEDULE

Lecture Time:

  • Tuesday: 3 pm – 6 pm (EA-06-03)

Instructors

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

Syllabus

Note: Information contained in this syllabus may be subject to change.

Week Topic
1
Jan12
Intro to the Course (NT)
Intro to Neurotechnology  (NT)
2
Jan19
Introduction of BioSignal Processing  (HR)
L1-CFT; L2-Stochastic Process/R.V./Moments/PSD
3
Jan26
Neural recording methods: Neural circuits, amplifiers, telemetry, stimulation (NT)
4
Feb2
Prepare Student Seminarspaper selection
Time-Frequency-Spatial Analysis  STFT (HR)
5
Feb9 (CNY)
Holidays
6
Feb16
Neural signals (clinical applications)- EEG, evoked potentials (HR)
Lab tutorial for Project I: Neural Signals and Analysis
Recess Feb22
7
Mar1
Multiple Dimensional  Signal Processing (HR)
Lab Project II: Application in neural systems
Student Reading Seminars (HR)
8
Mar8
Neuro Diagnostic and Therapeutic Devices by NT
9
Mar15
Brain machine interfaces  (NT)
EEG/ECoG
10
Mar22
Neuromorphic Engineering – Brain Inspired Robotics by SK
11
Mar29
Neuroimaging and Image Processing (HR)
Neuroimaging fMRI (HR)
12
Apr5
Advanced Neurosignal Processing / Neurosurgical systems (HR)
13
Apr12 (makeup)
Project Reports (due before final) & presentations (HR, NT)

Course Projects

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

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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Lectures and Guest Lectures

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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

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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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