BM

BTBME605B: Brain-Computer Interface Development Engineering Syllabus for BM 6th Sem 2019-20 DBATU (Elective-V)

Brain-Computer Interface Development Engineering detailed syllabus scheme for Biomedical Engineering (BM), 2019-20 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.

For 6th Sem Scheme of Biomedical Engineering (BM), 2019-20 Onwards, do visit BM 6th Sem Scheme, 2019-20 Onwards. For the Elective-V scheme of 6th Sem 2019-20 onwards, refer to BM 6th Sem Elective-V Scheme 2019-20 Onwards. The detail syllabus for brain-computer interface development engineering is as follows.

Brain-Computer Interface Development Engineering Syllabus for Biomedical Engineering (BM) 3rd Year 6th Sem 2019-20 DBATU

Brain-Computer Interface Development Engineering

Course Objectives:

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.
Get it on Google Play.

Course Outcomes:

  1. Learner will be able to understand the biophysical basis of non-invasive brain signals, to apply signal processing, discrimination, and classification tools to interpret these signals, and to implement these tools into a control system for a brain-computer interface.

Unit I

Hardware/Software Components Of Bci
Introduction, Components and signals, Electrodes, Bio signal amplifier, Real-time processing environment, Motor imagery, P300 spelling device, SSVEP, Accuracies achieved with different BCI principles, Applications-twitter, second life, smart home control with BCI

Unit II

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.
Get it on Google Play.

Unit III

Feature Extraction Methods In Classifying Eeg Signal For Bci
Introduction-Methods, Mutual information, Min max mutual information, Experimental setup, Data set, Results, P300-based BCI Paradigm Design- Event-Related Potentials (ERPs), P300 detection, Applications of P300.

Unit IV

Bci Based On The Flash Onset And Offset Vep
Introduction- Methods- Peak-to-valley amplitudes in the onset and offset FVEPs, Determination of gazed target, Usability of Transient VEPs in BCIs- VEPs, Availability of transient VEPs, Machine learning approach

Unit V

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.
Get it on Google Play.

Text Books:

  1. Reza Fazel-Rezai, “Recent Advances in Brain-Computer Interface Systems”, Intech Publications, First Edition, 2011.
  2. Theodre Berger W, John k Chapin et all, “Brain computer interfaces, An International assessment of research and developmental trends”, Springer, First Edition, 2008.

Reference Books:

  1. Guido Dornhege, “Toward brain-computer interfacing”, MIT Press, First Edition, 2007.

For detail syllabus of all subjects of Biomedical Engineering (BM) 6th Sem 2019-20 onwards, visit BM 6th Sem Subjects of 2019-20 Onwards.

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