Course Plan
(Spring Semester)
M. Tech. (Bioelectronics) : 2nd Semester
BE 504: Neuroengineering 

The integration of biomolecules with electronic elements to yield functional devices attracts substantial research efforts because of the basic fundamental scientific questions and the potential practical applications of the systems. The research field gained the buzzword "bioelectronics" aimed at highlighting that the world of electronics could be cross fertilized with biology and biotechnology. The major activities in the field of bioelectronics relate to the development of biosensors that transduce biorecognition or biocatalytic processes in the form of electronic signals. Neuroengineering, or more precisely Bioneuroengineering which is inseparable part of Bioelectronics, is an interdisciplinary area, with the common goal of analyzing the function of the nervous system, developing methods to restore damaged neurological function & creating artificial neuronal systems by integrating physical, chemical, mathematical & engineering tools. The development of artificial circuit models that simulate the behavior of biological neuron is one of today's most promising directions of investigation in the field of neurobio and neuromorphic engineering. 
Objective visavis Lecture Modules: 

Modules 
Topic 
Learning Objectives 
1 
Introduction 
Biology of the neuron, Biophysical description of the action potential, Synapses 
2 
Membrane 
Membrane transport, Membrane capacitance 
3 
HodgkinHuxley (HH) Model 
HH model of membrane, Membrane currents, Cable equation 
4 
Myelinated Nerve 
Electric circuit model of myelinated nerve 
5 
Neural modeling 
Linear dendritic model, Varicosities & impulse conduction, Information processing in dendrites 
6 
Silicon model of neuron 
HH model, synapse model, simple neuron logic gates. 
7 
Neuronal networks 
Neuronal networks, Neural coding 
Prerequisites: 
Basic understanding of Biology, Physiology of human body and basic knowledge of electronics is desired but not essential. 
Lecture Plan: 
Tentative lecture 
Topics 
1 
Introduction 
23 
Biology of the neuron 
45 
Biophysical description of the action potential 
68 
Synapses: Chemical Synapse, Electrical circuit model of synapse 
9 
Membrane transport 
10 
Membrane capacitance 
1112 
HodgkinHuxley (HH) Model of membrane 
1314 
Membrane currents 
1516 
Cable equation 
17 
Myelinated Nerve 
1819 
Electric circuit model of myelinated nerve 
2021 
Neural modeling: Linear dendritic model 
2223 
Varicosities & impulse conduction 
2425 
Information processing in dendrites 
2627 
Silicon model of neuron: HH model 
2829 
Synapse model, simple neuron logic gates 
3031 
Neuronal networks 
3233 
Neural coding 
Pedagogy: 
 Class Room Lectures
 Presentations

Expected outcome: 

After completing the course BE 522, student is expected to have the basic knowledge of the Bioneuroengineering and students are expected to work in the field of Bioneuro engineering as project work or as per their interest.

Text/Reference book: 
1. Grattarola, M.
Massobrio, G. Bioelectronics Handbook, MOSFETs, Biosensors & Neurons;
(McGraw Hill) 
BE 506: Bio medical Image Processing 

BE506 is an
introductory course into the field of Biomedical Image processing for M.Tech
in Bioelectronics (ECE) students. It covers mainly the concepts of
Biomedical image enhancement, restoration, compression, image transforms
etc.


Biomedical Image enhancement: To understand the concepts of image enhancement in spatial domain which includes several gray level transformations like image negatives, log transformations etc. To introduce the concepts related to histogram processing, use of arithmetic/logical operations and use of first and second derivatives for image enhancement. Biomedical Image restoration: To understand the concepts related to image degradation/restoration process using spatial filters like Inverse filter and Wiener filters. Image Transforms: To understand the concepts of unitary transforms and its properties, discrete Fourier transform, discrete cosine transform etc. Biomedical Image Compression: To understand the concepts of basic image compression, different challenges in biomedical image compression, some popular lossless and lossy compression techniques. Prerequisites of the course: Some understanding of Signals and Systems and Linear algebra will be required.

Lecture Plan: 

1. Introduction to Digital images and
Biomedical image processing technology: 3Hrs.

Pedagogy: 
 Class Room Lectures
 Presentations

Expected outcome: 

Students passing this course will be proficient with the knowledge of basic concepts of Biomedical imaging technology, enhancement, restoration and compression techniques. They will also have a basic knowledge of Image transforms, orthogonal transforms and its properties.

Text/Reference book: 
1. J.D. Bronzion, "Biomedical Engineering
Handbook", CRC press. 
BE 508: BioMEMS & Nanotechnology 

Microelectromechanical Systems (MEMS), an advanced product and equipment design concept, has already emerged in order to cater to the development of miniaturized products. It has become the preferred scenario for the next generation sophisticated products and equipment which are to be used to meet the aspectations of micro technology. Microdevices used for analysis and detection of biomedical and industrial reagents are under the scope of BioMEMS and finds applications in genetic screening, antibody gene expression in transgenic cells, biowarefare agents detection etc. Another aspect of this subject is the well known technology called nanotechnology and confines to the concepts of nanosensors, nanoarrays and nanodevices. BE 508 is a broad course to provide the students detail information as far as proof of principle, concepts, design, development and applications of MEMS, BioMEMS and Nanotechnology.

Objective visavis Lecture Modules: 

Modules 
Topic 
Learning Objectives 
1 
MEMS 
Origin of MEMS, Microfabrication and Micromachining, Market growth of MEMS technology, Microsensors and Microactuators, Transduction Principles in MEMS System on a Chip 
2 
BioMEMS 
Bio, Chemo, Micro Fluidic MEMS, ChemLab on a Chip, DNA Sensors 
3 
Nanotechnology 
Introduction to Nanotechnology, Nanotechnology Materials Carbon Nanotube (CNT), Applications of CNT 
4 
MEMS in Assistive 
ENose, ETounge, Artificial Auditory Chips, Artificial Vision Chips, Artificial Audio/ Visual Integrated Systems based on Brain Information Processing. 
Prerequisites: 
Basic understanding of 
Lecture Plan: 

Tentative lecture 
Topics 
1 
Introduction to MEMS 
2,3 
MEMS Sensor, MEMS Actuators 
4,5 
MEMS Sensing Principles 
6,7 
MEMS Actuation Principles 
8 
Intelligent sensors using MEMS 
9,10 
Micro pump 
11 
Micro cantilever beam 
12 
DNA Biosensors 
13,14 
Labona chip 
15 
Nanosensors 
16,17 
Nanodevices 
18,19 
ENose 
20 
Etongue 
21 
Artificial Auditory Chips 
22 
Artificial Vision Chips 
23,24 
Artificial audio/ visual integrated systems based on braininformation processing 
25 
An advanced Application of Modern Technology: daVinci System 
Pedagogy: 
 Class Room Lectures
 Presentations

Expected outcome: 
After completing the course BE 508, student is expected to have the basic knowledge of the advanced product and equipment design concept, design, development and applications of MEMS, BioMEMS and Nanotechnology.

Text/Reference book: 
N. P. Mahalik. MEMS. Tata McGraw Hill, 2008. 
BE 518: Bioelectronics system & control 
BE510 is a course into the field of control system engineering applied to bioelectronic system. It covers basic control system engineering theory , neural network and fuzzy logic control and application of this theory to bioelectronic system. 
Objectives: 
1. To give an introduction to basic
control system engineering principles. 
Prerequisites: 
Some understanding of mathematical modelling 
Lecture Plan: 

Tentative lecture 
Topics 
1 
To give an introduction to the subject 
24 
Control system types and representation 
57 
Mathematics of Control system theory ( system model, Laplace transform, Transfer function etc. ) 
812 
Analysis of Control system (Dynamic Response, Error and stability of control system ) 
1314 
Design and simulation of controllers 
1516 
Bode design and Nonlinear control System 
1726 
Fuzzy control theory and systems 
2730 
Neural networks and bioelectronic control systems 
3132 
Bioelectronic systems 
3337 
Some examples of Control theory applied to bioelectronic system modeling and analysis 
Pedagogy: 
 Class Room Lectures
 Presentations

Expected outcome: 
Towards the end of the course the student would be able to design, model and analyse control system in bioelectronic system.

Text/Reference book: 
1. Biosensors and Environmental
Monitoring; Author: U Bilitewski,A Turner; Publisher: Taylor and Francis.

BE 524: Advanced Bioelectronic Devices 
Metal  Oxide  Semiconductor (MOS):MOS Structure, Modes of operation, Metal
Oxide Semiconductor Field effect Transistor (MOSFET). 
Lecture Plan: 

Tentative lecture 
Topics 
15 
Unit 1: Metal  Oxide  Semiconductor (MOS): MOS Structure, Modes of operation, Metal Oxide Semiconductor Field effect Transistor (MOSFET). 
68 
Unit 2: Electrolyte Insulator  Semiconductor (EIS): EIS Structure, Site binding Theory, Electrical double layer theory. 
925 
Unit 3: MOSFET Based Bioelectronic devices Biosensor overview, Ion Sensitive Field Effect Transistor (ISFET), Enzyme Field Effect Transistor (ENFET), Chemical Field Effect Transistor (CHEMFET), Reference Field Effect Transistor (REFET), Immune Field Effect Transistor (IMFET), Organic Thin Film Transistor (TFT), CellBased Biosensors & Sensors of Cell Metabolism, Light Addressable Potentiometric Sensors (LAPS); Interfacing of Biological Systems with electronic systems, nonconventional bioelectronic devices, conducting polymer based ISFET. 
2630 
Unit 4: Modeling & Simulation SPICE and Electrochemical models of ISFET & CHEMFET. 
Pedagogy: 
 Class Room Lectures
 Presentations

Text/Reference book: 
1. Bioelectronics Handbook, MOSFETs,
Biosensors,& Neurons, Author: Massimo Grattarola, Giuseppe Massobrio,
Publisher: McGraw Hill. 