INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014
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UK: Managing Editor International Journal of Innovative Technology and Creative Engineering 1a park lane, Cranford London TW59WA UK E-Mail: editor@ijitce.co.uk Phone: +44-773-043-0249 USA: Editor International Journal of Innovative Technology and Creative Engineering Dr. Arumugam Department of Chemistry University of Georgia GA-30602, USA. Phone: 001-706-206-0812 Fax:001-706-542-2626 India: Editor International Journal of Innovative Technology & Creative Engineering Dr. Arthanariee. A. M Finance Tracking Center India 17/14 Ganapathy Nagar 2nd Street Ekkattuthangal Chennai -600032 Mobile: 91-7598208700
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014
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International Journal of Innovative Technology & Creative Engineering Vol.4 No.6 June 2014
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014
From Editor's Desk Dear Researcher, Greetings! Research article in this issue discusses about Segmenting Heart Sounds. Let us review research around the world this month; Elastic battery yarn could power smart clothes. Small, flexible electronics promise "smart" clothes of the future, such as T-shirts loaded with sensors that can discreetly keep track of your vital signs and check for health problems. Now Huisheng Peng and his colleagues at Fudan University in Shanghai, China, have created a thread-like battery that can be woven into smart textiles to keep them running smoothly. First, the team created wires made from carbon nanotubes nested inside each other. Some wires were coated with a powder of lithium titanium oxide nanoparticles, and others with lithium manganese oxide. One of each type of wire – representing the battery's positive and negative terminals – were twisted together with a gel electrolyte and a thin strip of non-conducting material separating them. A 10-centimetre-long piece of this battery weighs just 0.08 grams and can light a string of LEDs for up to a minute, the team reported. The researchers coiled the battery around an elastic thread to produce a stretchy power source. The threads could be bent and pulled hundreds of times without significant cost to their performance. Colour-changing metal to yield thin, flexible displays. Sheets of a unique alloy just a few nanometres thick take on different hues with the flick of a switch, offering a way to make full-colour displays for wearable computers such as Google Glass or smart contact lenses. The alloy germanium-antimony-tellurium (GST) can be switched between an amorphous phase, in which its molecular structure is disordered, and a highly ordered crystalline phase by the energy of a laser beam or electric current. The material is being explored for use in advanced memory chips, and is already being used in recording devices. For instance, when a laser is fired at a DVD coated in the alloy, the disc stores binary 0s and 1s as one of the two phases. The telltale reflectivity of each phase is then used to read back the data. Harish Bhaskaran and Peiman Hosseini at the University of Oxford were investigating the material's exotic optical properties, some of which appear when it is made into very thin films. Even online, emotions can be contagious. A face-to-face encounter with someone who is sad or cheerful can leave us feeling the same way. This emotional contagion has been shown to last anywhere from a few seconds to weeks. A team of researchers, led by Adam Kramer at Facebook in Menlo Park, California, was curious to see if this phenomenon would occur online. To find out, they manipulated which posts showed up on the news feeds of more than 600,000 Facebook users. For one week, some users saw fewer posts with negative emotional words than usual, while others saw fewer posts with positive ones. Digital emotions proved somewhat contagious, too. People were more likely to use positive words in Facebook posts if they had been exposed to fewer negative posts throughout the week, and vice versa. The effect was significant, though modest. It has been an absolute pleasure to present you articles that you wish to read. We look forward to many more new technologies related research articles from you and your friends. We are anxiously awaiting the rich and thorough research papers that have been prepared by our authors for the next issue.
Thanks, Editorial Team IJITCE
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Editorial Members Dr. Chee Kyun Ng Ph.D Department of Computer and Communication Systems, Faculty of Engineering, Universiti Putra Malaysia,UPM Serdang, 43400 Selangor,Malaysia. Dr. Simon SEE Ph.D Chief Technologist and Technical Director at Oracle Corporation, Associate Professor (Adjunct) at Nanyang Technological University Professor (Adjunct) at Shangai Jiaotong University, 27 West Coast Rise #08-12,Singapore 127470 Dr. sc.agr. Horst Juergen SCHWARTZ Ph.D, Humboldt-University of Berlin, Faculty of Agriculture and Horticulture, Asternplatz 2a, D-12203 Berlin, Germany Dr. Marco L. Bianchini Ph.D Italian National Research Council; IBAF-CNR, Via Salaria km 29.300, 00015 Monterotondo Scalo (RM), Italy Dr. Nijad Kabbara Ph.D Marine Research Centre / Remote Sensing Centre/ National Council for Scientific Research, P. O. Box: 189 Jounieh, Lebanon Dr. Aaron Solomon Ph.D Department of Computer Science, National Chi Nan University, No. 303, University Road, Puli Town, Nantou County 54561, Taiwan Dr. Arthanariee. A. M M.Sc.,M.Phil.,M.S.,Ph.D Director - Bharathidasan School of Computer Applications, Ellispettai, Erode, Tamil Nadu,India Dr. Takaharu KAMEOKA, Ph.D Professor, Laboratory of Food, Environmental & Cultural Informatics Division of Sustainable Resource Sciences, Graduate School of Bioresources, Mie University, 1577 Kurimamachiya-cho, Tsu, Mie, 514-8507, Japan Mr. M. Sivakumar M.C.A.,ITIL.,PRINCE2.,ISTQB.,OCP.,ICP Project Manager - Software, Applied Materials, 1a park lane, cranford, UK Dr. Bulent Acma Ph.D Anadolu University, Department of Economics, Unit of Southeastern Anatolia Project(GAP), 26470 Eskisehir, TURKEY Dr. Selvanathan Arumugam Ph.D Research Scientist, Department of Chemistry, University of Georgia, GA-30602, USA.
Review Board Members Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic & Ceramic Materials,CSIRO Process Science & Engineering Private Bag 33, Clayton South MDC 3169,Gate 5 Normanby Rd., Clayton Vic. 3168, Australia Dr. Zhiming Yang MD., Ph. D. Department of Radiation Oncology and Molecular Radiation Science,1550 Orleans Street Rm 441, Baltimore MD, 21231,USA Dr. Jifeng Wang Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign Urbana, Illinois, 61801, USA Dr. Giuseppe Baldacchini ENEA - Frascati Research Center, Via Enrico Fermi 45 - P.O. Box 65,00044 Frascati, Roma, ITALY. Dr. Mutamed Turki Nayef Khatib Assistant Professor of Telecommunication Engineering,Head of Telecommunication Engineering Department,Palestine Technical University (Kadoorie), Tul Karm, PALESTINE.
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014 Dr. Amala VijayaSelvi Rajan, B.sc,Ph.d, Faculty – Information Technology Dubai Women’s College – Higher Colleges of Technology,P.O. Box – 16062, Dubai, UAE
Naik Nitin Ashokrao B.sc,M.Sc Lecturer in Yeshwant Mahavidyalaya Nanded University Dr.A.Kathirvell, B.E, M.E, Ph.D,MISTE, MIACSIT, MENGG Professor - Department of Computer Science and Engineering,Tagore Engineering College, Chennai Dr. H. S. Fadewar B.sc,M.sc,M.Phil.,ph.d,PGDBM,B.Ed. Associate Professor - Sinhgad Institute of Management & Computer Application, Mumbai-Banglore Westernly Express Way Narhe, Pune - 41 Dr. David Batten Leader, Algal Pre-Feasibility Study,Transport Technologies and Sustainable Fuels,CSIRO Energy Transformed Flagship Private Bag 1,Aspendale, Vic. 3195,AUSTRALIA Dr R C Panda (MTech & PhD(IITM);Ex-Faculty (Curtin Univ Tech, Perth, Australia))Scientist CLRI (CSIR), Adyar, Chennai - 600 020,India Miss Jing He PH.D. Candidate of Georgia State University,1450 Willow Lake Dr. NE,Atlanta, GA, 30329 Jeremiah Neubert Assistant Professor,Mechanical Engineering,University of North Dakota Hui Shen Mechanical Engineering Dept,Ohio Northern Univ. Dr. Xiangfa Wu, Ph.D. Assistant Professor / Mechanical Engineering,NORTH DAKOTA STATE UNIVERSITY Seraphin Chally Abou Professor,Mechanical & Industrial Engineering Depart,MEHS Program, 235 Voss-Kovach Hall,1305 Ordean Court,Duluth, Minnesota 55812-3042 Dr. Qiang Cheng, Ph.D. Assistant Professor,Computer Science Department Southern Illinois University CarbondaleFaner Hall, Room 2140-Mail Code 45111000 Faner Drive, Carbondale, IL 62901 Dr. Carlos Barrios, PhD Assistant Professor of Architecture,School of Architecture and Planning,The Catholic University of America Y. Benal Yurtlu Assist. Prof. Ondokuz Mayis University Dr. Lucy M. Brown, Ph.D. Texas State University,601 University Drive,School of Journalism and Mass Communication,OM330B,San Marcos, TX 78666 Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic & Ceramic Materials CSIRO Process Science & Engineering Dr.Sumeer Gul Assistant Professor,Department of Library and Information Science,University of Kashmir,India Dr. Chutima Boonthum-Denecke, Ph.D Department of Computer Science,Science & Technology Bldg., Rm 120,Hampton University,Hampton, VA 23688
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014 Dr. Renato J. Orsato Professor at FGV-EAESP,Getulio Vargas Foundation,S찾o Paulo Business School,Rua Itapeva, 474 (8째 andar)01332-000, S찾o Paulo (SP), Brazil Dr. Wael M. G. Ibrahim Department Head-Electronics Engineering Technology Dept.School of Engineering Technology ECPI College of Technology 5501 Greenwich Road Suite 100,Virginia Beach, VA 23462 Dr. Messaoud Jake Bahoura Associate Professor-Engineering Department and Center for Materials Research Norfolk State University,700 Park avenue,Norfolk, VA 23504 Dr. V. P. Eswaramurthy M.C.A., M.Phil., Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India. Dr. P. Kamakkannan,M.C.A., Ph.D ., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India. Dr. V. Karthikeyani Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 008, India. Dr. K. Thangadurai Ph.D., Assistant Professor, Department of Computer Science, Government Arts College ( Autonomous ), Karur - 639 005,India. Dr. N. Maheswari Ph.D., Assistant Professor, Department of MCA, Faculty of Engineering and Technology, SRM University, Kattangulathur, Kanchipiram Dt - 603 203, India. Mr. Md. Musfique Anwar B.Sc(Engg.) Lecturer, Computer Science & Engineering Department, Jahangirnagar University, Savar, Dhaka, Bangladesh. Mrs. Smitha Ramachandran M.Sc(CS)., SAP Analyst, Akzonobel, Slough, United Kingdom. Dr. V. Vallimayil Ph.D., Director, Department of MCA, Vivekanandha Business School For Women, Elayampalayam, Tiruchengode - 637 205, India. Mr. M. Moorthi M.C.A., M.Phil., Assistant Professor, Department of computer Applications, Kongu Arts and Science College, India Prema Selvaraj Bsc,M.C.A,M.Phil Assistant Professor,Department of Computer Science,KSR College of Arts and Science, Tiruchengode Mr. G. Rajendran M.C.A., M.Phil., N.E.T., PGDBM., PGDBF., Assistant Professor, Department of Computer Science, Government Arts College, Salem, India. Dr. Pradeep H Pendse B.E.,M.M.S.,Ph.d Dean - IT,Welingkar Institute of Management Development and Research, Mumbai, India Muhammad Javed Centre for Next Generation Localisation, School of Computing, Dublin City University, Dublin 9, Ireland Dr. G. GOBI Assistant Professor-Department of Physics,Government Arts College,Salem - 636 007 Dr.S.Senthilkumar Post Doctoral Research Fellow, (Mathematics and Computer Science & Applications),Universiti Sains Malaysia,School of Mathematical Sciences, Pulau Pinang-11800,[PENANG],MALAYSIA.
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014 Manoj Sharma Associate Professor Deptt. of ECE, Prannath Parnami Institute of Management & Technology, Hissar, Haryana, India RAMKUMAR JAGANATHAN Asst-Professor,Dept of Computer Science, V.L.B Janakiammal college of Arts & Science, Coimbatore,Tamilnadu, India Dr. S. B. Warkad Assoc. Professor, Priyadarshini College of Engineering, Nagpur, Maharashtra State, India Dr. Saurabh Pal Associate Professor, UNS Institute of Engg. & Tech., VBS Purvanchal University, Jaunpur, India Manimala Assistant Professor, Department of Applied Electronics and Instrumentation, St Joseph’s College of Engineering & Technology, Choondacherry Post, Kottayam Dt. Kerala -686579 Dr. Qazi S. M. Zia-ul-Haque Control Engineer Synchrotron-light for Experimental Sciences and Applications in the Middle East (SESAME),P. O. Box 7, Allan 19252, Jordan Dr. A. Subramani, M.C.A.,M.Phil.,Ph.D. Professor,Department of Computer Applications, K.S.R. College of Engineering, Tiruchengode - 637215 Dr. Seraphin Chally Abou Professor, Mechanical & Industrial Engineering Depart. MEHS Program, 235 Voss-Kovach Hall, 1305 Ordean Court Duluth, Minnesota 55812-3042 Dr. K. Kousalya Professor, Department of CSE,Kongu Engineering College,Perundurai-638 052 Dr. (Mrs.) R. Uma Rani Asso.Prof., Department of Computer Science, Sri Sarada College For Women, Salem-16, Tamil Nadu, India. MOHAMMAD YAZDANI-ASRAMI Electrical and Computer Engineering Department, Babol "Noshirvani" University of Technology, Iran. Dr. Kulasekharan, N, Ph.D Technical Lead - CFD,GE Appliances and Lighting, GE India,John F Welch Technology Center, Plot # 122, EPIP, Phase 2,Whitefield Road,Bangalore – 560066, India. Dr. Manjeet Bansal Dean (Post Graduate),Department of Civil Engineering ,Punjab Technical University,Giani Zail Singh Campus, Bathinda -151001 (Punjab),INDIA Dr. Oliver Jukić Vice Dean for education, Virovitica College, Matije Gupca 78,33000 Virovitica, Croatia Dr. Lori A. Wolff, Ph.D., J.D. Professor of Leadership and Counselor Education, The University of Mississippi, Department of Leadership and Counselor Education, 139 Guyton University, MS 38677
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Contents A Novel and Robust Method for Segmenting Heart Sounds by Averaging Neighbors by K. Lakshmi Devi and Dr. M. Arthanari…………………………………………………………………………………………….……………………….[216]
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014
A Novel and Robust Method for Segmenting Heart Sounds by Averaging Neighbors K. Lakshmi Devi Research Scholar, Mother Teresa Women’s University, Kodaikanal, Tamil Nadu, India. K.lakshme@yahoo.com Dr. M. Arthanari Dean, Dept of Science & Humanities, Nehru Institute of Technology Coimbatore, India arthanarimsvc@gmail.com Abstract - A novel method for segmenting heart sounds is proposed. The Algorithm composes of filtering the heart sound signal by Discrete Wavelet Transform(DWT), smoothing by moving average filters, detecting peaks with automatic threshold and Labeling of S1 and S2 sounds. In this study, the signal is normalized and decomposed using ‘daubechies-30’ wavelet. The algorithm handles High intensity murmurs and high background noise that lacks in Homomorphic Filtering and Shannon energy methods. The proposed method achieved better performances with 95% and 93% segmentation accuracies of S1 and S2.
Keywords: PCG, Peak detection, Segmentation of sounds, DWT.
Threshold,
valves during each cardiac cycle. The first heart sound is low and associated with the vibrations set up by the sudden closure of the mitral tricuspid valve during the ventricles contract and pump blood with the aorta and pulmonary artery at the start of the ventricular systole[3,4]. The second sound S2 is a shorter highpitched sound caused when the ventricles stop ejecting, relax and allow the aortic and pulmonary valves close just after the end of the ventricular systole. S1 has duration of about 0.15s and the frequency ranges from 25-45Hz. S2 has duration of about 0.12s and has 50Hz frequency. The signal has to be manipulated so as to
I. INTRODUCTION
Reliable Authentication and Identification is becoming increasingly important in many fields where information security is facing issues on illegal copying and sharing of digital media. Knowledge-based or possession-based access control methods proved to be immortal. Biometric authentication system offers several advantages over traditional authentication at the time and point of authentication. It is difficult to forge biometric traits and they seem to be powerful. Each trait has its own strength and weakness and the choice depends on the Application. Cardiac Auscultation uses natural signals called Heart sounds for health monitoring and diagnosis for thousands of years. Heart sounds contain great information to provide unique identity for each person. The heart produces two biological signals, the Electrocardiogram (ECG) and Phonocardiogram (PCG). Like ECG readings, these signals are difficult to disguise and therefore reduces falsification. Heart sounds are discrete bursts of auditory vibrations of varying Intensity (loudness), frequency (pitch), quality and duration[1]. Two sounds namely S1 and S2 are normally generated as blood flows through the heart
Fig. 1. Time-Frequency representation of Heart Sounds
gain useful features that have to involve for the process of identification. II. EXISTING SYSTEM
Segmenting Heart sounds is a crucial task in the study of PCG signals for identification and authentication. Heart sound signals are decomposed into wavelet energies and an adaptive threshold is used to discriminate S1/S2 sounds from murmurs. Gupta et.al segmented using Homomorphic filtering and k-means clustering. This technique converts a non-linear combination by applying logarithmic transformation.
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014 Liang et.al segmented heart sounds based on envelograms. Multi band wavelet Shannon energies are used. Olmez et.al segmented using wavelet energies. Bentley used polyfit function to fit that point and its neighborhood with parabola. It focused on the segmentation and classification based on wavelet decomposition combined with spectrogram analysis. When compared to the previous approaches, olmez’s approach gave performance with a process time of 0.76s and achieved 91.47% success in segmenting S1 and 88.95% success in segmenting S2.
The peaks are determined by calculating the average of the distance between its neighbors. The threshold value is automatically calculated. The locations of the heart sounds are computed with time intervals. The aim is to have a pathology-independent recognition system that is capable of separating sounds from murmurs.
Segmentation by Homomorphic filtering and Shannon energy methods were slightly affected from noise. The envelope analysis approach needs elimination of the extra peaks while retaining the ones that correspond to the fundamental heart sound. III. PROPOSED SYSTEM
Our aim is to increase the performance rate in segmenting S1 and S2. The overall authentication needs manipulation of the signal which involves signal capturing, amplification of the signal and remove noise, changing a signal to emphasize certain characteristics, training and Matching and Identity verification. Fig.2 shows the overall authentication process. This study exposes the pre-processing stage of the whole process. Accurate segmentation is needed for further processing. Signal
capt uring
Fig. 3. Discrete Wavelet Transform
A. Windowing
Windowing is decomposing Heart signals into frames of length N ending at time m. For simplicity, Rectangular windowing function was used.
Preprocessing Frame Selection emalization Segmentation of S1 and S2
W(n) =
1, 0≤n≤N-1
0 , otherwise
Normalization
where N is the length of the window in samples. Each frame is chosen such that it has one full cardiac cycle with 20ms of frame length and 5ms of overlapping time.
Filtering by Wavelet transform
Input Signal
`
1 0
Feature Extraction
-1
0
1
2
3
4
5
6
7
8 5
x 10 Downsampled to 2000Hz
Classification
0.5 0
Fig. 2. Cardiac Biometrics Authentication Process
-0.5
In this system, multi-pass moving average filters smooth the sum of the up-sampled third, fourth and fifth-level wavelet coefficients. A particular time-frequency representation commonly used in heart sound analysis is the discrete wavelet transform (DWT). DWT based features are easy to implement. Moreover, the coefficients are unaffected by the type of envelope detection method used, since they are calculated directly from heart sound signals. The smoothed output gives an apparent output of the locations of S1 and S2.
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0
20
40
60
80
100
120
140
160
12
14
16
180
Normalized Signal 1 0 -1
0
2
4
6
8
10
18 4
x 10
Fig. 4. Normalized Signal
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014 th
B. Normalization The windowed samples are normalized to remove offsets. The original signal was down sampled to 2000Hz and normalized by (|
( ) ( )|)
The detailed coefficients of 3, 4 &5 level (D3, D4 & D5) are taken for the amplification of the signal. The outputs are up-sampled and summed for emphasizing the difference between S1 and S2 sounds. Fig. 5 shows the output of the decomposition at level 5 which sums the detail coefficients D3, D4 and D5. D.
where x2000(t) is the value of the down sampled signal at time t. Fig. 4 shows the normalized signal after down sampling by 2000Hz. C. Wavelet Energies
Segmentation
Multi-pass Moving Average Filters: The Actual Heart sound signal still has very complicated patterns with numerous spikes that has little impact on diagnosis but may influence the location of S1 and S2[5].
The DWT analyzes the signal at different frequency bands with different resolution. There are characteristics that define the wavelet Analysis: the irregularity and the asymmetry of the wavelet mother functions, and the variable length of windows to better adapt to the frequency components being analyzed. These characteristics make the wavelet analysis suitable for the surveillance related sound events, which frequently present a short duration and impulsive characteristics [2]. According to Nyquist’s rule, the signal can be subsampled by two, simply by discarding every other sample as depicited in fig.3. The signal is decomposed th by using daubechies 5 order wavelet method. The Daubechies wavelet family is selected because of its orthogonal property, accuracy and computational inexpensiveness. As S1 and S2 fall within the range of frequencies 30-250Hz and considering 2000Hz sampling frequency, fifth decomposition level detail coefficients produce the best output. Studies indicate that segmentation by wavelet energies show higher performance and Accuracy [4]. Heart sound features with the highest frequency are murmurs which are up to 600Hz [5]. So this decomposition, depicted in Table 1, removes high intensity murmurs which HMF algorithms fail to achieve. Table 1 describes the different frequency bands obtained through the transform. TABLE I
Fig. 5. Matlab Output for the 3rd, 4th and 5th Detailed Coefficients
Hence the signal is smoothed. If both signal and noise are present, these two can be partially separated by looking at the amplitude of each frequency. One of the difficulties in implementing this and other is that the overlap-add method for filtering signal is not valid. A typical approach is to divide the original time domain signal into overlapping segments. After processing, a smooth window is applied to each of the overlapping segments before they are recombined. This provides a smooth transition of the frequency spectrum from one segment to the next. Moving Average Filters operate by taking the average of the number of points from the Input signal to produce each point in the output signal, given by the equation
DECOMPOSED LEVELS AND FREQUENCIES
Sub signal st
1 level, D1 2
nd
Frequency Bands 500-1000Hz
level, D2
250-500Hz
3 level, D3
rd
125-250Hz
th
62.5-125Hz
th
31.25-61.5Hz
th
15.6-31.25Hz
4 level, D4 5 level, D5 6 level, D6
[]
∑ [
]
where M is the number of points in the average. The highest amplitude can be attributed and the noise can be discarded, it is set to zero. Multi-pass involves passing the input signal through a MAF two or more times. Two passes are equivalent to using a ‘triangular’ smoothing. This is explicitly good smoothing filters. The biggest difference in this filter when compared to others is execution speed. It is the fastest digital filter available.
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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.6 JUNE 2014 2) Peak Detection by Averaging Neighbors: The Peak is the highest point between ‘valleys’. It means that there are lower points around it. Slopes greater than zero amplitude are taken into consideration. Let X=[x1, x2, … xi,… xN] be a given uniformly sampled signal containing periodic peaks, where N is the length of the signal. Let Y=[ y1, y2, … yi,… yN] be their corresponding amplitudes. xi be the given ith point in X. The search exists till the length of the signal, from left to right. Let L be the set of k samples of highest amplitude, to the left of the ith point in xi in X. Let R be the set of highest amplitude to the right of the ith point of xi in X. The peak function is defined as the average of the maximum of L and R. ( )
algorithm gave higher accuracies of 95% of S1 and 93% of S2 segmentations. The segmentation accuracies resulted when tested on a subset of Heart sound database. It is the result of the number of sounds segmented without errors to the total number of heart sounds in the database. Multiple passes will be correspondingly slower, but still very quick. In comparison, Gaussian, triangular filters are excruciatingly slow, because they must use convolution. Not only is the moving average filter very good for many applications, it is optimal for a common problem, reducing random white noise.
( )
TABLE II PERFORMANCE OF DIFFERENT METHODS
A given point xi in X is a peak if a function F(i, xi) ≥ h,
Method
Where h is a threshold value obtained by Ma, ven, Genderen and Beukelman(2005) [6]. They compute the threshold automatically as h = (max+ abs_avg)/2+k*abs_dev If the computed peak function F is greater than or equal to the threshold then it is considered a peak. For this one and a half cycle of heart sound, three peaks are found. Among different values, it is found that k=1, gives the best value.
if no. of peaks>1 {
Process time
Performance S1
S2
Wavelet Energy Method
0.76s
91.47%
88.95%
Wavelet Shannon Energies
0.83s
84.94%
81.19%
Homomorphic Filtering Method
0.37s
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Proposed Method
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93%
V. CONCLUSION AND FUTURE WORK
Store peak_dist= current peak position-previous peak Position; } If the peak distance between the 1st and 2nd peak is greater than the time interval between 2nd and 3rd, then the peaks are named as S2-S1-S1 else it is S1-S2-S1, as the distance between a systole and a diastole is shorter than the distance between a diastole and a systole.
In this paper we have explained a preliminary phase on the implementation of the Identification system with biological traits. Information taken from a single cardiac cycle plays an important role. So identifying a single cycle and its characteristics give accurate results for further study. We proposed a method to segment the heart sounds to identify S1 and S2 without the presence of murmurs. In the near future, automated verification system is to be implemented by emphasizing features of the heart sounds.
IV. EXPERIMENTAL EVALUATION Heart sounds are recorded with Digital Stethoscope with 16-bit accuracy and a sampling frequency of 2000Hz. A database of 20 PCG sequences comprising of heart sounds of different pathologies from 20 people, both male and female, are taken for the study. Each sound is a .WAV file and is of 70s of length. The proposed
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REFERENCES
[1] Walker HK, Hall WD, Hurst JW. Clinical methods: The History, Physical and laboratory Examinations, 3rd Edition.
[2] Valero, X. Alias. F. Gammatone Wavelet features for sound classification in surveillance applications. 2012. In the proceedings of the 20th European Signal Processing Conference.
[3] Kokosoon Phua, J. Chen, Tran.H. Louis shue. 2007. Heart Sound as a Biomteric. In Pattern Recognition Society.
[4] Mustafa Yamach,
Zumray Dokur, Tamer Olmez. 2008. Segmentation of S1-S2 sounds in Phonocardiogram Records using Wavelet Energies. In IEEE.
[5] Yiqi Deng, peter J.bentley. A Robust Heart Sound Segmentation and classification Algorithm using Wavelet Decomposition and Spectrogram.
[6] Meng Ma, Van Genderen, Peter Beukelman. 2005. Developing and Implementing Registration.
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