BN5209
Neurosensors and Signal Processing (2010/2011, Semester 2) 

 MODULE OUTLINE Created: 14-Aug-2006, Updated: 13-Jan-2013
 
Module Code BN5209
Module Title Neurosensors and Signal Processing
Semester Semester 2, 2010/2011
Modular Credits 4
Faculty Engineering
Department Biomedical Engineering
Timetable Timetable/Teaching Staff
Module Facilitators
PROF Li Xiaoping Coordinator
Weblinks
Tags --


Learning Outcomes | Schedule | Syllabus | Assessment | Workload | References


 LEARNING OUTCOMES Top
This module teaches students the electrical and magnetic field of the human brain in relation to the brain activities and methods for sensing the electrical and magnetic field of human brain in relation to brain activities. Major topics include: the electric and magnetic field of the brain in relation to brain activities, sensors for measuring the electric field and magnetic field of the brain in relation to brain activities, digitization of brain activities - neural waves, characterization of neural waves, neural power map and neural matrix brain activity pattern recognition using neural power map and neural matrix, and applications of brain activity monitoring. The module is designed for students at Master and PhD levels in Engineering, Science and Medicine.


 SCHEDULE Top
 

 

 

 

 

 

 

 

Week #

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

 

Week 1

 

 11-Jan-11 (Tuesday, E3 06-10)

 

 

 

 

 

 

Introduction - the electrical field and magnetic field of the brain (I)

4pm-6pm

 

 

 

 

 

Lecturer: Dr Shen Kaiquan, Department of Mechanical Engineering

               Prof Einar Wilder-Smith, Department of medicine

              

 

 

 

 

Week 2

 

 18-Jan-11

 

 

 

 

 

 

Introduction - the electrical field and magnetic field of the brain (II)

4pm-6pm

 

 

 

 

 

 

Lecturer: Dr Shen Kaiquan, Department of Mechanical Engineering

               Prof Einar Wilder-Smith, Department of medicine

 

 

 

 

 

Week 3

 

 25-Jan-11

 

 

 

 

 

 

MEG - SQUID sensors and MEG machine using SQUID

4pm-6pm

 

 

 

 

 

 

Lecturer: Dr. Zhao Zhenjie, Department of Mechanical Engineering

 

 

 

 

 

Week 4

 

 1-Feb-11

 

 

 

 

 

 

MEG measurement using SQUID

4pm-6pm

 

 

 

 

 

 

Lecturer: Dr. Zhao Zhenjie, Department of Mechanical Engineering

 

 

 

 

 

Week 5

 

 8-Feb-11

 

 

 

 

 

 

EEG - basic principles, electrodes and devices

4pm-6pm

 

 

 

 

 

 

Lecturer: Prof Li Xiaoping, Department of Mechanical Engineering & Division of Bioengineering

 

 

 

 

 

 

Week 6

 

 15-Feb-11

 

 

 

 

 

 

EEG measurement and comparison between EEG and MEG

4pm-6pm

 

 

 

 

 

 

Lecturer: Prof Li Xiaoping, Department of Mechanical Engineering & Division of Bioengineering

 

 

 

 

 

Recess Week

 

 22-Feb-11

 

 

 

 

 

 Recess Week

 

Week 7

 

 1-Mar-11

 

 

 

 

 

Mid-semester Break

Lab Project (I) - EEG measurement

4pm-6pm

 

 

 

 

 

 

Lecturer: Prof Li Xiaoping, Department of Mechanical Engineering & Division of Bioengineering

 

Week 8

 

 8-Mar-11

 

 

 

 

 

 

Neural waves and brain activities

4pm-6pm

 

 

 

 

 

 

Lecturer: Dr Shen Kaiquan, Department of Mechanical Engineering

               Prof Einar Wilder-Smith, Department of medicine

 

 

 

 

 

Week 9

 

 15-Mar-11

 

 

 

 

 

 

Neural signal processing (I) - the waveform method

4pm-6pm

 

 

 

 

 

 

Lecturer: Dr Shen Kaiquan, Department of Mechanical Engineering

               Prof Einar Wilder-Smith, Department of medicine

 

 

 

 

 

Week 10

 

 22-Mar-11

 

 

 

 

 

 

Lab Project (II) - EEG measurement for brain activities

4pm-6pm

 

 

 

 

 

 

Lecturer: Prof Li Xiaoping, Department of Mechanical Engineering & Division of Bioengineering

 

 

 

 

 

Week 11

 

 29-Mar-11

 

 

 

 

 

 

Neural signal processing (II) - the dynamic spatial power mapping method

4pm-6pm

 

 

 

 

 

 

Lecturer: Prof Li Xiaoping, Department of Mechanical Engineering & Division of Bioengineering

 

 

 

 

 

Week 12

 

 5-Apr-11

 

 

 

 

 

 

Lab Project (III) - EEG pattern recognition for brain activity monitoring

4pm-6pm

 

 

 

 

 

 

Lecturer: Prof Li Xiaoping, Department of Mechanical Engineering & Division of Bioengineering

 

 

 

 

 

Week 13

 

 12-Apr-11

 

 

 

 

 

 

Summary

4pm-6pm

 

 

 

 

 

 

Lecturer: Prof Li Xiaoping, Department of Mechanical Engineering & Division of Bioengineering

 

 

 

 

 

Reading Week

18-Apr-11

19-Apr-11

20-Apr-11

21-Apr-11

22-Apr-11

23-Apr-11

 

 

Reading Period

 

Examination

25-Apr-11

26-Apr-11

27-Apr-11

28-Apr-11

29-Apr-11

30-Apr-11

 

Examination period

Examination

2:30pm-4:30pm

 

 

Examination

 2-May-11

 3-May-11

 4-May-11

 5-May-11

 6-May-11

 7-May-11

 

Examination period

 

                           


 SYLLABUS Top

1. Introduction - the electrical field and magnetic field of the brain

2. EEG sensors - the theories and designs

3. MEG sensors - the theories and designs

4. Neural waves and brain activities

5. Characterization of brain activities

6. Characterized brain activity pattern recognition

7. Applications of brain activity monitoring

Three laboratory sessions are included: 1) sensors for the electrical field and magnetic field of the brain; 2) measurement of the electrical and magnetic field of the brain in relation to brain activities; 3) signal processing. Group projects will be carried out on EEG measurement for unintentional sleep onset and other brain activities.



 ASSESSMENT Top

Laboratory projects - 30%

Final examination - 70%



 WORKLOAD Top
2 lecture hours per week.
0 tutorial hours per week.
0 lab hours per week.
1 hour for projects, assignments, fieldwork etc per week.
7 hours for preparatory work by a student per week.


 
 1. TEXT & READINGS Top
Total 2 items
Title and AuthorEdition / Year /
*ISBN
Publisher
Bioelectromagnetism,
Author:J. Malmivuo and R. Plonsey
- / 1995
ISBN:
Oxford University PressCompulsory
Magnetism in Medicine
Author:W. Andra and H. Nowak
- / 1998
ISBN:
WILEY-VCHReferences



Learning Outcomes | Schedule | Syllabus | Assessment | Workload | References