Centre for Biomedical Engineering

Course Title

Biostatistics

Course number

BMC6010

Credits

4

Course Category

PC (Program Core)

Pre-requisite

Introductory course on Probability and Statistics

Contact Hours (L-G-P)

3-1-0

Type of Course

Theory

Course Objectives

This course aims at providing the necessary basic concepts in probability, random processes and introductory statistics. Knowledge of fundamentals and applications of phenomena will greatly help in the understanding of topics such as estimation and detection, pattern recognition, signal processing.

Course

Outcomes

At the end of the course the students will be able to

1.      Understand and characterise phenomena which evolve with respect to time in probabilistic manner. Acquire skills in handling situations involving more than one random variable.

2.      Understand the concept of random process and be able to analyse and solve the problems.

3.      Have a basic knowledge of statistics and its usage.

4.      To be able to apply statistical concepts to problems.

Syllabus

Lecture

Unit-I: Probability Distributions and Random Variables

Probability: basic probability model, Bayes rule, Conditional probability, Random Variables: Distribution and density functions, Expectation, Moments, Multiple Random Variables: Joint Distribution and Joint Density Function, Independence, Covariance and Correlation, Central limit theorem

16

Unit-II: Random Processes

Concept of a Random Process - Classification, Ergodicity, Stationarity and Independence, Time averages and Ensemble averages, Correlation Functions and its properties, Gaussian and Poisson Random Process

08

Unit-III: Basic Statistics

Measures of Central tendency: Moments, Skewness and Kurtosis; Probability distributions: Binomial, Poisson and Normal; Correlation and Regression.

12

Unit-IV: Applied Statistics

Descriptive measures of engineering data, sampling distributions, estimation of mean and variance, confidence intervals, hypothesis testing, linear regression

12

Total No. of Lectures

48

Books*/

References

1.   George R. Cooper and Clare D. McGillem, “Probabilistic Methods of Signal and System Analysis”, 3^rd edition, Oxford University Press, 2007

2.   Peyton Z. Peebles Jr., “Probability, Random Variables and random Signal Principles”, 4^th edition, McGraw Hill Education, 2017.

3.   R. E. Walpole, R. H. Myers, S. L. Myers, K. E. Ye, “Probability and Statistics for Engineers,” Pearson, 2014.

4.   R. A. Johnson, Probability and Statistics for Engineers, PHI

5.   J H Zar, Biostatistical Analysis, Pearson Education.

Course Assessment/

Evaluation/

Grading Policy

Sessional

Assignments / Quiz / Presentations

15 Marks

Mid Term Examination

25 Marks

Sessional Total

40 Marks

End Semester Examination

60 Marks

Total

100 Marks

Course Title

Anatomy and Physiology

Course number

BMC6020

Credits

4

Course Category

PC (Program Core)

Pre-requisite

-

Contact Hours (L-G-P)

3-1-0

Type of Course

Theory

Course Objectives

This course aims to provide the necessary basic knowledge of Medical Science to students with engineering background. It will help in understanding and working with living system and to apply advanced technology to the complex problems of Medicare

Course

Outcomes

At the end of the course the students will:

1.    have a basic knowledge of terminology, level of organization, tissue of the body and general anatomy of skin, muscles, nerve, vessels, bones and  joints.

2.    be able to apply knowledge of human biology in understanding the design of the instruments

3.    be able to describe and discuss the physiological basis of various mechanisms operating in various organs and systems of the body. 

4.    develop critical reasoning skills in its application to biomedical engineering.

Syllabus

Lecture

Unit-I:

Levels of organization and tissues of the body (cell, tissues of the body), Introduction to skin and fascia, Introduction to Skeletal system(cartilage and bone), Muscular system (general feature, type, structure & function of muscles, innervations of skeletal muscle, Joints (including definition, classification and movements, Nervous system (subdivision of N.S, nervous tissue, spinal cord and spinal segments, receptors, reflex arc, nerve fibre and their myelination, ANS).

12

Unit-II:

Introduction and anatomy of respiratory system; Introduction and anatomy of heart; Introduction and anatomy of GIT tract; Introduction and anatomy of excretory system; Anatomy and classification of endocrine system

12

Unit-III:

Cell Physiology - Functions and transport across cell; Nerve Muscle Physiology – Resting membrane potential and Action potentials in excitable tissue, Types of muscle and their mechanism of contraction, Structure and properties of neuromuscular junctions; Central Nervous System (CNS)- Organization of CNS, Synapse, Motor and sensory system, Maintenance of posture and balance, Basal ganglia; Special Senses- Physiology of vision and hearing

11

Unit-IV:

Respiratory System – Mechanics of breathing, Ventilation -perfusion, Transport of gases, Regulation of respiration; Cardiovascular- Basics of ECG, Cardiac output, Regulation of cardiovascular system; Gastro-intestinal – GI motility, Physiological functions of Liver, gall bladder, intestine and pancreas; Endocrinology – Mechanism of hormone action, Hormones of Pituitary, Thyroid, Parathyroid, Adrenal Gland, Adrenal Cortex; Renal – Mechanism of Urine formation, physiology of Acid- Base Balance

13

Total No. of Lectures

48

Books*/

References

1. R Drake, A W Vogl, A Mitchell, Gray’s Anatomy for Students, 4^th edition, Elsevier 2020

2.     B D Chaurasia,  Human Anatomy , 7^th edition, CBS publisher, 2017

1. B D Chaurasia, Handbook of General Anatomy, CBS publisher, 2009

4.     I Singh, Textbook of Human Histology with color atlas and practical guide, 8^th edition, Jaypee Brothers Medical Publishers; 2016.

5.     J E Hall, Guyton and Hall Textbook of Medical Physiology, 13^th edition, Elsevier, 2015.

Course Assessment/

Evaluation/

Grading Policy

Sessional

Assignments / Quiz / Presentations

15 Marks

Mid Term Examination

25 Marks

Sessional Total

40 Marks

End Semester Examination

60 Marks

Total

100 Marks

Course Title

Bioinstrumentation

Course number

BME6110

Credits

4

Course Category

PE (Program Elective)

Pre-requisite

-

Contact Hours (L-T-P)

3-1-0

Type of Course

Theory

Course Objectives

The students will know the fundamental concepts of biomedical instrumentation and develop their ability to analyze the signals and solve problems. It also aims to explain the principles of and ways in which to build the instrumentation, including different kinds of sensors.

Course

Outcomes

At the end of the course the students will be able to

1. Develop a clear knowledge about human physiology system.

2. Understand various methods of acquiring biosignals.

3. Analyze and evaluate the principles of various biomedical devices and sensors.

4. Describe and design the instrumentation for amplifying the bioelectrical signals.

Syllabus

Lecture

Unit- I: Introduction

Physiology: Cell and its structure, Resting and Action Potentials, Propagation of Action Potentials, Nervous system – CNS –PNS – Nerve cell – Synapse, Cardio pulmonary system, Physiology of heart and lungs

12

Unit – II: Virtual Instrumentation:

Bioelectric Potentials – ECG, EEG, EMG, MEG, Electrophysiological measurements: Bio potential Electrodes, Lead systems and recording methods –Typical waveforms, Bioelectric amplifiers; Interference in Biosignals

12

Unit – III: Sensors:

Transducers and Sensors characteristics, Transducers for biomedical applications, Transducers for Body temperature, Blood pressure& respiration rate, Sensor performance characteristics and Intelligent sensors, Classify medical instruments based on different principles

12

Unit – IV: Data Acquisition Methods:

Introduction to Medical Imagining equipment, Characteristics , generation and application of x-ray, Ultrasound and its applications in medical instrumentation, Computer tomography, magnetic resonance imaging, Defibrillator Machine, blood cell counter, blood gas analyzer

12

Total No. of Lectures

48

Books*/

References

1.    R S Khandpur, Hand Book of Bio-Medical instrumentation, Tata McGraw Hill, 2003.

2.    L Cromwell, F J Weibell, E A Pfeiffer, Biomedical Instrumentation and Measurements, 2^nd edition, Pearson Education India, 2015.

3.    J. J. Carr, J M Brown, Introduction to Biomedical Equipment Technology, 4^th edition, Pearson Education, 2002

4.    J G Webster, Medical Instrumentation, John Wiley & Sons, 2005

5.    NPTEL lectures/notes and MIT open courseware

6.    Relevant journals/ Magazines / Transaction papers.

Course Assessment/

Evaluation/

Grading Policy

Sessional

Assignments / Quiz / Presentations

15 Marks

Mid Term Examination

25 Marks

Sessional Total

40 Marks

End Semester Examination

60 Marks

Total

100 Marks

Course Title

Data Acquisition and Analysis

Course number

BME6140

Credits

4

Course Category

PE (Program Elective)

Pre-requisite

-

Contact Hours (L-G-P)

3-1-0

Type of Course

Theory

Course Objectives

This course aims to develop in the student the ability to evaluate, the most appropriate strategy for acquiring data. Also to develop the understanding of a range of modern time and frequency domain analysis techniques as well as advanced applications such as data fusion.

Course

Outcomes

At the end of the course the students should have

1.      Basic knowledge of LabVIEW and its use for data acquisition and analysis.

2.      The ability to design and implement a data acquisition solution to a problem.

3.      The ability to apply data analysis techniques to the data in both time and frequency domains.

Syllabus

Lecture

Unit-I: Virtual Instrumentation:

Basics of virtual instrumentation. Introduction to LABVIEW: Loops, Data structures, Arrays and Clusters, Graphs and Charts, File Input/Output, Developing VI and sub VIs for data analysis and presentation.

10

Unit-II: Data Acquisition

Sensors, Data acquisition, Signal conditioning and processing techniques, analogue-to-digital converters, Sampling,   Development of acquisition and display systems using the DAQ Assistant to Generate LabVIEW Code.

10

Unit-III: Data Analysis - I

10

Data pre-processing, digital filtering, Data Visualisation (2-D and 3-D), Statistical properties of signals, time and frequency domain, convolution and correlation, Spectral Analysis

Unit-IV:  Data Analysis - II

Curve fitting and data modelling, interpolation and extrapolation, non-stationary signal analysis, Development of analysis systems of biomedical signals.

10

Content beyond syllabus:

Data analysis using Python/Matlab.

08

Total No. of Lectures

48

Books*/

References

1.    B Mihura*, LabVIEW for Data Acquisition, Prentice Hall of India, 2013.

2.    R M. Rangayyan*, Biomedical Signal Analysis, second edition,  IEEE Press, USA, 2015.

3.    J G Webster, Medical Instrumentation: Application and Design, 4th edition, John Wiley & Sons, 2009.

4.    Labview for students, https://www.ni.com/en-in/shop/labview/select-edition/labview-student-edition.html.

5.    Python for informatics by Charles Severance (available online).

6.    Python for Everybody, Exploring Data Using Python 3 by Charles R. Severance (available online)

Course Assessment/

Evaluation/

Grading Policy

Sessional

Assignments / Quiz / Presentations

15 Marks

Mid Term Examination

25 Marks

Sessional Total

40 Marks

End Semester Examination

60 Marks

Total

100 Marks