1.
APPLICATION OF DSP
IN BIOMEDICAL
ENGINEERING
BY: 14ES38(GL),14ES112,14ES28,14ES72,14ES44

2.
AGENDA
• BACKGROUND INFOMATION
• INTRODUCTION
• APPLICATION OF DSP IN BIOMEDICAL ENGINEERING
• ECG
• HEARING AID
• MRI
• MEDICINE
• CONCLUSION
• REFERENCES

3.
BACKGROUND INFORMATION
• A historical trend of the last half-century is the replacement of
analog signals by digital signals.
• [1] It was in the 1960s that a discipline of digital signal processing
began to form.
• Two very important advantages to digital signals:
i. Digital signals can be reproduced exactly
ii. Digital signals can be manipulated easily.
• Today digital signal processing is a major branch of engineering.

4.
INTRODUCTION
• DSP SYSTEM:
• Without DSP, it would not be easy to analyze and visualize data and
perform their design, and so on.
• DSP is very often used method in a biomedical engineering research.
• Medical instruments would be less efficient for precise diagnoses if there
were no digital electrocardiography (ECG) analyzers or digital x-rays and
medical image systems.

5.
APPLICATION OF DSP IN BIOMEDICAL
ENGINEERING
DSP APPLICATIONS
EEGMEDICINEMRI
HEARING
AID

6.
HEARING AID
• A hearing aid is simply an electronic sound amplifier.
• You've seen people on stage speak into a microphone and have
their voices hugely amplified by giant loudspeaker so crowds can
hear them.
• A hearing aid works exactly the same way, except that the micro
phone, amplifier, and loudspeaker (and the battery that powers
them) are built into a small, discreet, plastic package worn behind
the ear.
• Types: Analog Hearing Aid and Digital Hearing Aid

7.
ANALOG HEARING AID

8.
DIGITAL HEARING AID(DSP OR DIGITAL
SIGNAL PROCESSOR)

9.
ADVANTAGES
ANALOG HEARING AID
• Generally cost less than digital
hearing aids
• Are sometimes more powerful
than digital hearing aids
• Long time hearing aid users
sometimes prefer analog over
digital
DIGITAL HEARING AID
• Can be programmed with noise
reduction algorithms to help
reduce background noise
• Highly programmable for
various listening environments
• Most flexible and adjustable for
specific user needs

10.
MRI
 A real-time-time cardiac magnetic resonance imaging (MRI) system
has been implement using digital signal processing (DSP)
technology.
 The system enables real-time acquisition, processing and display of
cardiac movies at moderate video rates of 20 images/sec.

11.
WHAT IS MRI
 Hydrogen atom nucleus (proton) is acting as micro magnet.
 Human body is full of proton in every organ and tissues but with
different concentration in different structure.
“That’s where the “M” agnetic of MRI comes from”

12.
 Each proton is rotating around its axis as 63,000,000
rotation per second
 now we need to capture the emitted energy from RF
coil.
When the RF power is sent (at 63MHz), protons from
whole body respond.
It is needed to select certain “slice” to image

13.
Now the 63MHz RF pulse excites only the 63MHz slice that’s the
“R”esonance of MRI comes from
Remember human body is 3D, slice direction can be determined by using
any of three(x,y,z) gradient i:e. Axial, Sagittal, Coronal

14.
MEDICINE

15.
WHAT IS BLOOD PRESSURE?
Description:
• Blood pressure is one of physiological variables,
• Sphygmomanometer, which determines the blood pressure with
other means ,such as heart signals.
• BP indicates the force with which blood is driven through the heart.
• It is divided into two sections
i)Systole
ii)Diastole

16.
THE ACQUISITION OF A BLOOD
PRESSURE SIGNAL
• A blood pressure (BP) signal contains clinically relevant
components up to about 20 Hz.
• The signal is contaminated by noise at the mains frequency (50Hz)
and other noise (mainly below 50 Hz) may also be present.
• Now ,what should be sampling rate?

17.
EEG
 EEG stand for electro-encephalo-graph
 Recording of electrical signals from human brain
 signal's parameters and patterns indicate the health of the brain
 EEG is the key area of biomedical data analysis
 DSP functions are used to analyze the EEG signals

18.
CHARACTERISTICS AND ORIGIN OF
BRAIN WAVES

19.
DSP BASED ANALYTICAL METHODS
 Spectral estimation
 Periodogram
 Maximum entropy method
 AR method
 ARMA method
 Maximum likelihood method

20.
CONCLUSION
• The importance of DSP in biomedical engineering is quite clear
now.
• Without DSP, it would not be convenient for doctors to give proper
treatment to patient.
• Results would be uncertain without DSP.
• Efficiency of medical instruments is enhanced using DSP.

21.
REFERENCES
 http://ethw.org/Digital_Signal_Processing [1]
 https://www.ncbi.nlm.nih.gov/pubmed/10504098
 citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.595.4711&rep=rep1...
 http://www.slideshare.net/kanusinghal3/medical-applications-of-
dsp?next_slideshow=1
 https://www.isip.uni-luebeck.de/uploads/tx_wapublications/EEG_DWT_01.pdf
 http://www.eeherald.com/section/design-guide/dg100008.html