ISSN 2277-6176 (Online) ISSN 2321-4252 (Print)
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Current Trends in Signal Processing
Contents
1. Efficient Partial Update Algorithm over Wireless Networks Rupali Dewda, Vijay Barfa
1
2. Elimination of Noise on ECG Signal Using Adaptive Filter ShabnamTahmin, Zeenat Afroze
9
3. Non-invasive Extraction of Fetal Electrocardiogram and Maternal Electrocardiogram from Mixed Source Signal Sai S. Kulkarni, Supriya O. Rajankar
16
4. Congenital Heart Disease (CHD) Detection Technique Based on Analysis and Classification of ECG Signal Pravin Baburao Kamble, D.T. Ingole 23 5. Heater Automation Using LabVIEW N. Dinesh Kumar, Ch V.B. Aditya Kumar
28
6. Performance Evaluation of Direction of Arrival Estimation in Smart Antenna S.S. Jadhav, D.G. Ganage, S.A. Wagh
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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
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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 timevarying 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,
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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
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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 abovementioned 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 noninvasive, 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: đ?‘Śđ?‘– (đ?‘Ą) = [đ?‘Ś1 (đ?‘Ą), đ?‘Ś2 (đ?‘Ą), ‌ , đ?‘Śđ?‘ (đ?‘Ą)]đ?‘‡ . Using the ICA model this is generated as: đ?‘Śđ?‘– (đ?‘Ą) = đ??ľđ?‘&#x;đ?‘– (đ?‘Ą) (1) Where; đ?‘&#x;đ?‘– (đ?‘Ą) the vector of n-dimension and its elements are termed as the sources. While đ??ľđ?‘›âˆ—đ?‘› is termed as unknown mixing matrix. Therefore the source estimation can be written as: đ?‘˘(đ?‘Ą) = đ?‘Šđ?‘Ľđ?‘– (đ?‘Ą) = đ?‘Šđ??ľđ?‘&#x;đ?‘– (đ?‘Ą) (2)
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Congenital Heart Disease (CHD) Detection Technique Based on Analysis and Classification of ECG Signal Pravin Baburao Kamble1,*, D.T. Ingole2 1
Department of Electronics, Amravati University, Maharashtra, India Department of Electronics, Ram Meghe Institute of Engineering, Amravati, Maharashtra, India
2
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 defectrelated 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
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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
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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 waveletbased 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, minnorm, 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.
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