Current Trends in Signal Processing vol 6 issue 3

ISSN 2277-6176 (Online)

ISSN 2321-4252 (Print)

Current Trends

in Signal Processing(CTSP)

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STM JOURNALS

1. Efficient Partial Update Algorithm over Wireless Networks Rupali Dewda, Vijay Barfa 1

2. Elimination of Noise on ECG Signal Using Adaptive FilterShabnamTahmin, Zeenat Afroze 9

3. Non-invasive Extraction of Fetal Electrocardiogram and Maternal Electrocardiogram from Mixed Source SignalSai S. Kulkarni, Supriya O. Rajankar 16

4. Congenital Heart Disease (CHD) Detection Technique Based on Analysis and Classification of ECG SignalPravin Baburao Kamble, D.T. Ingole 23

5. Heater Automation Using LabVIEWN. Dinesh Kumar, Ch V.B. Aditya Kumar 28

6. Performance Evaluation of Direction of Arrival Estimation in Smart AntennaS.S. Jadhav, D.G. Ganage, S.A. Wagh 39

ContentsCurrent Trends in Signal Processing

CTSP (2016) 1-8 © STM Journals 2016. All Rights Reserved Page 1

Current Trends in Signal Processing ISSN: 2277-6176(online), ISSN: 2321-4252(print)

Volume 6, Issue 3

www.stmjournals.com

Efficient Partial Update Algorithm over Wireless

Networks

Rupali Dewda*, Vijay Barfa

Department of Electronics and Communication, Rishiraj Institute of Technology, Indore,

Madhya Pradesh, India

Department of Electronics, Hathway Cable and Datacom Ltd., Indore, Madhya Pradesh, India

Abstract Adaptive partial update algorithm is developed based on incremental method. The proposed

algorithm applies in real time changing environment. The proposed algorithm responds to

linear estimation with nodes in cooperative manner and less number of computations. The

algorithm has powerful advantage is that it requires less number of coefficient and reduced

computational and communication complexity in wireless sensor network. It is efficient

because it has power of solving distributed estimation and optimization by learning

mechanism. In wireless sensor networks there are various applications that involve

phenomenon in which space parameter are varying like surveillance, environment monitoring,

battle field, precision agriculture and medical application. In this paper three algorithms;

sequential partial update, stochastic partial update and max partial update are compared in

terms of mean square error (MSE). Performance characteristic and complexity analysis of

each algorithm are compared with MATLAB simulation.

Keywords: Incremental network, Sequential partial update, stochastic partial update, Max

partial update, MSE

INTRODUCTION A wireless sensor networks (WSNs) composed

of an array of sensor nodes, i.e., tiny

embedded devices, which are distributed in the

geographical area, which collect information

or investigate special events and communicate

in a wireless manner [1]. The adaptive

distributed strategy, which relies on the

incremental mode, is the process of

cooperation between distinct nodes; these

nodes perform local computation and share the

result with the neighbouring nodes. The

resulting algorithm is cooperative, distributed,

and able to respond in real time change in

environment [2]. The nodes, which we also

interchangeably call agents, consist of at least

three main components: process units, sensing

devices and a wireless transmit-receive unit. In

more advance sensor networks, nodes are also

equipped with actuators to take action

according to the command issued from a

control unit.

Due to their vast applications, efficient design

and implementation of wireless sensor

networks have become an area of current

research [2]. Since the nodes in a network

function with small and limited battery power

and usually nonrenewable resources, it is

important to design the networks with less

communication among the nodes to estimate

the required parameter vector because

communication and computation consumes

most of the energy [2, 3]. Adaptive distributed

strategies with incremental mode of

communication focused on reduction in

communication complexity among the nodes

by restricting a particular node receiving and

transmitting to the predefined immediate

nodes only instead of every node of the

network [4, 5].

In this paper, we study and develop distributed

adaptive strategies for monitoring time-

varying physical phenomenon in sensor

network under real-world limitation and

change in environment condition.

In this paper, incremental partial update

strategies are proposed for weight update,



Volume 6, Issue 3

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Elimination of Noise on ECG Signal Using Adaptive Filter

ShabnamTahmin*, Zeenat Afroze

Department of Electrical and Electronics Engineering, American International University-Bangladesh,

Bangladesh

Abstract There are various biomedical signals present in the human body, by examining these

biomedical signal one can check the health condition of a person who is clinically fit or not.

Electrocardiogram (ECG) is one of them. ECG plays an important role in the primary

diagnosis, prognosis and survival analysis of heart diseases. This ECG signal is corrupted by

various noises like power line interference, baseline wandering etc. One way to remove this

noise is filtering the signal. This paper will present the performance of adaptive filter on ECG

signal. Diseases can be found by mixing power line interference with the ECG signal. We

have used the advanced adaptive filtering technique with Least Mean Square Algorithm for

the removal of power line interference from the ECG signal. Also, we have changed different

parameter of adaptive filter and we analyzed the performance of algorithm in terms of Signal

to Noise Ratio (SNR) improvement.

Keywords: ECG Signal, adaptive filter, least mean square (LMS), signal to noise ratio (SNR)

INTRODUCTION The electrocardiograph (ECG) is an

instrument, which records the electrical

activity of the heart. A cleaned ECG signal

provides necessary information about the

electrophysiology of the heart diseases and

ischemic changes that may occur. It provides

valuable information about the functional

aspects of the heart and cardiovascular system.

The ECG works mostly by detecting and

amplifying the tiny electrical changes on the

skin that are caused when the heart muscle

"depolarizes" during each heartbeat. This is

detected as tiny rises and falls in the voltage

between two electrodes placed either side of

the heart, which is displayed as a wavy line

either on a screen or on a paper [1]. This

display indicates the overall rhythm of the

heart and weaknesses in different parts of the

heart muscle, so it is very important to get the

ECG signal clean and free from noise [1].

ECG signal generated from human body are

often very weak so as to be easily covered by

background noise. The noise in the ECG

signals occur due to various reasons like

electromagnetic interference due to ubiquitous

supply lines and plugs, movement of patient,

signals generated by other organs and

impedance mismatching between electrodes

[2]. Hence, the ECG signals can be corrupted

by various types of noises such as Power line

interference, Electrode contact noise, Motion

artifact, Muscle contraction, Base line drift,

Instrumental noise generated by electronic

devices [2]. ECG signal has frequency range

from 0.5 to 80 Hz and power line interference

introduces 50 to 60 Hz frequency component

in that signal which is the major cause of

corruption of ECG. Various methods have

been employed for the removal of power line

interference from ECG signals. One of them is

using an adaptive filter.

SIGNIFICANT FEATURES OF ECG

WAVEFORM ECG records carrier information about

abnormalities or responses to certain

stimulating in the heart. Some of the

characteristics of these signals are the

frequency and morphology of their waves.

These components are in the order of just a

few up to 1 mV and their frequency content

within 0.5 and 100 Hz depending on

individual [3]. The morphology and frequency

are analyzed by physicians in order to detect

heart disorders and heart related pathologies.

A typical scalar electrocardiographic lead is

shown in Figure 1, where the significant



Volume 6, Issue 3

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Non-invasive Extraction of Fetal Electrocardiogram and

Maternal Electrocardiogram from Mixed Source Signal

Sai S. Kulkarni*, Supriya O. Rajankar Department of Electronics and Telecommunication, Sinhgad College of Engineering, Pune,

Maharashtra, India

Abstract This paper is to bring in self-regulating methodology to obtain Fetal Electrocardiogram

(FECG) and Maternal Electrocardiogram (MECG) from the mixed source signal. The

Abdominal Electrocardiogram (AECG) is treated as an input signal to achieve the above-

mentioned goal. FECG and MECG can be differentiated according to the power of a signal.

FECG are weak signals as compared to that of MECG. But, FECG signals are engrossed in

various other interference signals and thus its extraction has gained significance in the

medical field. Various other methods and research work were done in this field. This paper is

focused on non-invasive methods and by implementing independent component analysis.

Various mathematical calculations are used in order to get accurate FECG signal. Then after

‘R’ peaks can be calculated and later fetal heart rate which will help to know the condition of

the fetus in mother’s womb.

Keywords: Abdominal electrocardiogram, blind source separation, fetal electrocardiogram,

independent component analysis, maternal electrocardiogram

INTRODUCTION An intense research for detecting the condition

of a fetus at the possibility of damage or

demise in the uterus was carried out. Thus,

monitoring the condition of fetus during

pregnancy is one of the important parameters.

The monitoring of a fetus can be done by

invasive as well as non-invasive methods.

Being on the safer side, the researchers,

scientist and the doctors believe in non-

invasive, i.e., harmless methodology to extract

fetal Electrocardiogram (FECG). Useful

information of fetus can be obtained by means

of fetal Electrocardiogram (FECG). For

example, fetal academia, fetal hypoxia, and

fetal acidosis can be diagnosed by fetal heart

rate pattern, duration of ST-segment and

changes observed in QT interval and the T

wave respectively [1].

When the electrodes are placed on the

abdomen of a pregnant woman, abdominal

electrocardiogram (AECG) is obtained. This

AECG consists of FECG as well as MECG in

addition of other noises. Using the concept of

blind source separation, an algorithm named

independent component analysis can be used

to differentiate FECG signals and MECG

signals. FECG signals are of very low voltage

as compared to MECG signals. ICA

(Independent Component Analysis) helps to

extract FECG but not suited for real time

application as it requires high order statistics

and thus prior database is required to carry out

the procedure without any obstacles [2].

PREPROCESSING TECHNIQUES Before the application of ICA algorithm, some

basic preprocessing techniques are used in

order to improve the efficiency of the output

results.

Let us consider mixed source signal, y as the

n-dimensional vector:

𝑦𝑖(𝑡) = [𝑦1(𝑡), 𝑦2(𝑡), … , 𝑦𝑁(𝑡)]𝑇. Using the ICA

model this is generated as:

𝑦𝑖(𝑡) = 𝐵𝑟𝑖(𝑡) (1)

Where; 𝑟𝑖(𝑡) the vector of n-dimension and its

elements are termed as the sources. While 𝐵𝑛∗𝑛

is termed as unknown mixing matrix. Therefore

the source estimation can be written as:

𝑢(𝑡) = 𝑊𝑥𝑖(𝑡) = 𝑊𝐵𝑟𝑖(𝑡) (2)



Volume 6, Issue 3

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Congenital Heart Disease (CHD) Detection Technique

Based on Analysis and Classification of ECG Signal

Pravin Baburao Kamble1,*, D.T. Ingole

2

1Department of Electronics, Amravati University, Maharashtra, India

2Department of Electronics, Ram Meghe Institute of Engineering, Amravati, Maharashtra, India

Abstract As per American Heart Association information, every year 125 babies out of 1000 are born

with congenital heart disease (CHD). It was estimated that 36000 children are live born with

CHD each year in the European Union. Child with CHD may have hole in heart up to 3–5 mm

as small defects and for large defects it may go up to 5–8 mm. Depending upon the size of

hole in the upper or lower chamber of heart shows diseases such as atrial septal defect (ASD),

ventricular septal defect (VSD), patent ductus arteriosus (PDA) and tetralogy of Fallot (TOF).

Child patients with CHD report difficulties in several areas of daily life such as sports, study,

travelling, and driving. It affects the efficiency and functionality of heart. It also affects the

autonomic control of heart rate. The main focus would be to detect CHD in the pediatric

population and preventive measures that can be proposed to improve the quality of life.

Nowadays, we still fill infancy in the analysis of pediatric ECG. In our research work, we

aimed at wave detection of CHD and its ECG analysis with different classification techniques

so that child with CHD can be diagnosed accurately. We then attempted to justify the

recommendation for promising future directions in signal processing and database creation.

Keywords: atrial septal defect (ASD), ventricular septal defect (VSD), patent ductus

arteriosus (PDA), tetralogy of Fallot (TOF)

INTRODUCTION Heart defects are among the most common

birth defects and lead to cause birth defect-

related deaths [1]. The heart is a pumping

organ and has four chambers. The two upper

chambers are called right atrium (RA) and left

atrium (LA) and the two lower chambers are

called right ventricle (RV) and left ventricle

(LV). The upper chambers are separated by a

wall called interatrial septum and the lower

chambers are separated by another wall called

interventricular septum. Pulmonary artery

takes impure blood to the lungs for

purification and Aorta carries pure rich blood

to the whole body [2].

Congenital heart defect (CHD) simply means

that the heart developed problems since when it

was being formed in the womb. It is a heart

problem that baby is born with. It can include

abnormal development of the heart, the heart

valves, major arteries or combination of these

problems. The atrial septal defect (ASD) is hole

in the upper chamber of heart. The ventricular

septal defect (VSD) is hole in the wall between

the right and left ventricles. The patent ductus

arteriosus (PDA) is an opening between

pulmonary artery and the aorta through which

pure blood intended for the body is directed

back to the lungs. The wave detection of these

diseases and analysis of waves P-QRS-T would

help the pediatric population.

Electrocardiogram (ECG) system helps to

collect data in terms of P-QRS-T wave with

the help of various filters and after collection

of data we can analyze it. Fetal ECG was first

observed by M. Cremer in 1906 [3]. Early

works in this area were performed by using the

galvanometric apparatus of that time, which

were limited by very low amplitude of fetal

signals. As measurement and amplification

techniques improved, fetal ECG (FECG)

became more feasible and popular [4, 5]. In the

1960s, intrauterine electrodes provided SNR

improvement for FECG analysis [6]; but it was

not applicable to the premature heart due to

identification problem. Shortly afterwards, with

the developments in computer science and

signal processing techniques, automatic signal



Volume 6, Issue 3

www.stmjournals.com

Heater Automation Using LabVIEW

N. Dinesh Kumar*, Ch V.B. Aditya Kumar Department of Electronics and Communication Engineering, Vignan Institute of Technology and

Science, Deshmukhi, Nalgonda, India

Abstract Water heating system is an age-old tradition being commonly used from domestic sectors to

production sectors; it is a need-based requirement to develop all time and effective water

heating system for use in day-to-day life. With reference to lime lighting the deficiencies in

general water heating systems and improved versions of sensor operated systems, this model

has been designed. The scope of the work is specifically with reference to common household

water heating systems operated using LabVIEW software, facilitating absence of an

individual. Water heaters without control of water level indicator and energy cut off

orientation will cause short circuits in domestic, commercial environments. Intelligent

application of sensors used in the devices will balance the total losses of different kinds and

ensure utmost satisfactory service to the domestic as well as commercial users. In the public

interest and routing out the common man’s water heating problems, the model will deliver the

efficiency oriented water heating systems with cost effectiveness.

Keywords: LabVIEW, heating element, tank, pump, temperature sensor, set point, geyser

INTRODUCTION Supplying of hot water for domestic as well as

commercial, (i.e., multipurpose) users, by

adopting sensor oriented thermodynamic

heater system without manual supervision,

through which users save time and money.

Though varieties of water heating systems

have emerged in this market, the special

features of this model destine in exhibiting the

auto cutoff of the heater as well as overflow of

water. In addition, the heater will not get

started until there is minimum level in the

geyser [1].

Many water-heating systems are manufactured

based on the concept of continuous supply of

water and current. In the absence of water in

the geyser, if the power supply is made on the

thermostats, coils gets fused off and lot of

damage in the form of short circuit results.

Whereas the latest phenomenal approach like

sensor based auto cut off power supply/water

level indicators, which will save the device as

well as the total power supply system from the

mains. When on commercial use, the impact of

normal water boiling systems without the

advanced techniques will cause human loss

and infrastructure loss due to the blasts, which

occur in the units. By using the automation

techniques in water heating systems, even a

layman can operate the systems without any

extra skills. As the systems are cost effective,

need based automation devices they can

deliver required loads without any power

damage. Thus, anybody can afford to install

this type of sensor-based devices, which are

lifetime dependable and definitely will save

time and money in a longer way.

So this model is constituted on the ideology of

controlling the functions like overflow of tank,

over heating of the system, water level

parameters and auto-cutoff facility. So, the

concept of sensor based heater systems with

unique features like no supply of power to

heater without attaining minimum water levels

and auto cut off of power as well as

temperature of water, will serve the needs of

domestic as well as commercial users. This

type of heaters built with modern scientific

techniques will not only save money but also

save consumption of power and water [2].

IMPLEMENTATION USING

LabVIEW The model is mainly designed and developed

using the software and hardware components

within the ambit of LabVIEW. LabVIEW is a



Volume 6, Issue 3

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Performance Evaluation of Direction of Arrival

Estimation in Smart Antenna

Raju Dara, Bhongir Sony

Department of Electronics and Telecommunication, Sinhgad College of Engineering, Pune,

Maharashtra, India

Abstract Direction of arrival (DOA) estimation has typically played a key role in signal processing. Its

task is to find the directions impinging on an array antenna to increase the performance of the

received signal. To use DOA estimation methods that are applicable to most environments has

become the key of technique implementation. The traditional algorithms can get superior

performance for DOA estimation in the rich receiving conditions, but they are not fit for

adverse environment such as low SNR, small number of array elements or snapshots, etc. In

order to improve the performance of DOA estimation, the modified method based on wavelet

operator is used. Moreover, the method is applied on DOA estimation algorithm multiple

signal classification (MUSIC) to get new algorithm WMUSIC. Undoubtedly, the wavelet-

based method expands the application range of traditional DOA estimation algorithms and

has widely practical prospects in future. Further results are improved to minimize the errors

in angle estimation by using genetic algorithm.

Keywords: Direction of arrival, MUSIC, SNR

INTRODUCTION The array signal processing is fast developing

in the last decades [1]. Accurate DOA

estimation will bring many significant

advantages, such as increasing the capacity,

reducing the transmitter power of mobile

terminal, resisting multipath effect, decreasing

interference from outside, and so on [2]. The

various algorithms are proposed successively

in recent years, including capon, high-order

cumulate method, propagator method, min-

norm, MUSIC and ESPRIT, among which

MUSIC is considered to be high resolution and

accuracy method [3]. However, much of the

previous studies show that the performance of

the most DOA estimation algorithms depends

on some factors, such as the number of array

elements and spatial distribution, the number

of snapshots, and signal-to-noise ratio (SNR)

of received array signals [4].

In the light of wavelet transform having the

powerful ability on noise reduction, we

developed a new signal receive model based

on wavelet operator to improve original

methods for estimating DOA. In this report,

we propose modified method called as

WMUSIC, which combines wavelet operator

with MUSIC method to estimate DOA. By

utilizing wavelet transform to filter lots of

noise from the received array signals, DOA of

news de-noised signals can be estimated by

MUSIC method. The modified WMUSIC can

get superior performance even under weak

communication environment. In contrast to the

traditional MUSIC, the modified method can

improve greatly both resolution and accuracy

of DOA estimation. Therefore, the problem of

DOA estimation can be resolved for WMUSIC

under lower SNR.

ARRAY SIGNAL RECEIVED MODEL Most DOA estimation methods, which are on

signal processing, rely on certain assumptions

made on the received array signals. In the

section, the 2D pattern is used to describe

briefly the model of DOA as follows:

As shown in Figure 1, we considered a

scenario with emitting sources from different

directions with narrowband property, and we

have a linear antenna array with element to

receive each emitting signal.

ISSN 2277-6176 (Online)

ISSN 2321-4252 (Print)

Current Trends

in Signal Processing(CTSP)

September–December 2016

SJIF: 3.649

www.stmjournals.com

STM JOURNALSScientific Technical Medical

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