Brain Computer Interface and Applications detailed syllabus for Instrumentation & Control Engineering (ICE) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the ICE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Instrumentation & Control Engineering 6th Sem scheme and its subjects, do visit ICE 6th Sem 2021 regulation scheme. For Professional Elective-V scheme and its subjects refer to ICE Professional Elective-V syllabus scheme. The detailed syllabus of brain computer interface and applications is as follows.
Course Objectives:
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Unit I
INTRODUCTION TO BCI
Fundamentals of BCI – Structure of BCI system – Classification of BCI – Invasive, Non-invasive and Partially invasive BCI – EEG signal acquisition – Signal Preprocessing – Artifacts removal.
Unit II
ELECTROPHYSIOLOGICAL SOURCES
Sensorimotor activity – Mu rhythm, Movement Related Potentials – Slow Cortical Potentials-P300 -Visual Evoked Potential – Activity of Neural Cells – Multiple Neuromechanisms.
Unit III
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Unit IV
FEATURE TRANSLATION METHODS
Linear Discriminant Analysis – Support Vector Machines – Regression – Vector Quantization-Gaussian Mixture Modeling – Hidden Markov Modeling – Neural Networks.
Unit V
APPLICATIONS OF BCI
Functional restoration using Neuroprosthesis – Functional Electrical Stimulation, Visual Feedback and control – External device control, Case study: Brain actuated control of mobile Robot.
Course Outcomes:
On successful completion of this course, the student will be able to
- Describe BCI system and its potential applications.
- Analyze event related potentials and sensory motor rhythms.
- Compute features suitable for BCI.
- Design classifier for a BCI system.
- Implement BCI for various applications.
Text Books:
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Reference Books:
- R. Spehlmann, “EEG Primer”, Elsevier Biomedical Press, 1981.
- Arnon Kohen, “Biomedical Signal Processing”, Vol I and II, CRC Press Inc, Boca Rato, Florida, 1986.
- Bishop C.M., “Neural Networks for Pattern Recognition”, Oxford, Clarendon Press, 1995.
For detailed syllabus of all the other subjects of Instrumentation & Control Engineering 6th Sem, visit ICE 6th Sem subject syllabuses for 2021 regulation.
For all Instrumentation & Control Engineering results, visit Anna University ICE all semester results direct link.