GIAN Course on Practical Biological Signal Analysis

Course Contents:

Introduction to biological signal analysis
Discrete-time signals and systems
Introduction to Matlab with exercises
Spectral analysis
Signal conditioning
Digital filtering
Matlab exercises: introducing ECG signals, reducing noise from ECG signals, analysing ECG spectral content and filtering
Feature extraction
Classification
Matlab exercises: feature extraction, classification of EEG signals
Mini group project: Attendees to work on real world problem solving exercise involving ECG signal

Uploads:

Analysing biological signals such as electrocardiogram and electroencephalogram has become very important with modern healthcare striving to provide cost effective point-of care diagnosis and personalised treatment. Furthermore, fast computing power in recent years has made much of the more complex analysis methodologies possible.
The aim of this course is to provide attendees with a fundamental understanding of signal processing techniques and classification algorithms for analysing biological signals. The course will allow the attendee to demonstrate understanding of basic principles of digital signals; awareness of physiology and characteristics of different biological signals; describe and apply pre- and post- processing techniques, such as conditioning, filtering, feature extraction, classification and statistical validation techniques for biological signals and solve practical biological signal analysis problems using the industry standard software, MATLAB.
Simpler approaches will be followed in the delivery of the course. Mathematics will be used only where necessary and when used (and where possible), numerical examples that are suitable for paper and pencil approach will be given. There will plenty of illustrations(‘picture speaks thousand words’) to aid the attendee in understanding the signal analysis methods and the results of applying the methods. Several examples of recently studied real life biological signal analysis applications will also be discussed.
The main strength of the course is that it will discuss all four related sections to biological signal analysis: signal preprocessing, feature extraction, classification algorithms and statistical validation methods.

Objectives:

The aim of this course is to provide students with an understanding of the fundamentals of signal processing and classification algorithms for analysing biological signals. After completing this module, attendees will be expected to be able to:

Demonstrate an understanding of basic principles of digital signals and classification of different digital signals
Demonstrate an understanding of different biological signals
Describe and apply pre- and post- processing techniques, such as conditioning, filtering, feature extraction, classification and hypothesis testing techniques for different biological signals
Solve real world biological signal analysis problems

Teaching Faculty:

Dr Palaniappan Ramaswamy
Reader
School of Computing
University of Kent
United Kingdom
Email: r.palani@kent.ac.uk

Coordinator:

Professor K. Chandrasekaran
Department of CSE,
NITK Surathkal,
+91-824-2474000 Extn. 3400, 3044

Co - coordinator:

Dr. Shyam Lal
Assistant Professor,
Department of E&C,
NITK Surathkal,
+91-824-2473522
Email: shyam.mtec@gmail.com

Dr Palaniappan Ramaswamy is currently a Reader in the School of Computing, University of Kent, which is a top 20 UK university. His research interests include biological signal processing, brain-computer interfaces, biometrics, neural-networks, genetic-algorithms, and image processing. To date, he has written three text books in engineering and published over 150 papers (with over 2000 citations) in peer-reviewed journals, book chapters, and conference proceedings. He is a senior member of the Institute of Electrical and Electronics Engineers and member in Institution of Engineering and Technology. He is also the Editor-in-Chief of International Journal of Cognitive Biometrics and editorial board member for several international journals. He also serves in the prestigious Peer Review College for UK Research Councils and many other international grant funding bodies. He has supervised more than half a dozen postgraduate students to completion and has more than 18 years of multi-disciplinary teaching experience in computer science and engineering (electrical and biomedical) disciplines. His pioneering work on revolutionary new areas of brain-computer interfaces and emerging biometrics has not only received international awards and recognition by the scientific community but also from the media and public. His international research collaborations on signal processing and machine learning include among others institutions from Canada, China, India, Malaysia and Singapore.

Registration Starts: October 21, 2016

Registration Closes: November 10, 2016

Selection Notification: November 11, 2016

Event Date: November 21, 2016 to November 25, 2016

Online registration is MUST to attend this course.

Before registration read the instructions given below:

Registration Procedure:

Fill the registration form that was sent with Brochure.
Pay the registration fee (if applicable) as DD.
Scan the duly filled registration form and the DD (PDF format only accepted).
Go to the online registration link: http://www.cse.l3.nitk.ac.in/upcoming-events/gian/bio-signal-analysis/registration
Fill the registration form and upload the scanned documents on or before November 10, 2016.
Acceptance notification will be sent by E-mail.

Note: Number of participants for this course is limited to 50.

Registration Fee:

PARTICIPANT FROM	FEES *
Industry / Research Organization	Rs. 10,000/-
Academic Institutions	Rs. 5,000/-

* The above fee includes all instructional materials, computer use and internet facility. The participants will not be given any TA/DA and boarding / lodging support. Participant can bring their laptop for effective utilization of course delivery.

Note: Faculty / student of NITK will be admitted at free of cost.

Payment Details:

Payment Mode	In Favour of	Payable at
Only Demand Draft (DD)	COMSIM	Surathkal or Mangalore

Shared accommodation can be arranged to the registered participants on request in NITK Guest house or International Hostel (FCFS basis). However, participants are informed that Hotel accommodation is also available at Surathkal or Mangalore City. Kindly send your accommodation request to techevents.cse@gmail.com.

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