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Leung, Terence Sze-tat. "Time-frequency characterisation of paediatric heart sounds." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287001.
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Andersson, Gustav. "Classification of Heart Sounds with Deep Learning." Thesis, Umeå universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149699.
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Health care is becoming more and more digitalized and examinations of patients from a distance are closer to reality than fiction. One of these examinations would be to automatically classify a patient-recorded audiosegment of its heartbeats as healthy or pathological. This thesis examines how it can be achieved by examining different kinds of neural networks; convolutional neural networks (CNN) and long short-term memory networks (LSTM). The theory of artificial neural networks is explained. With this foundation, the feed forward CNN and the recurrent LSTM-network have their methods described. Before these methods can be used, the required pre-processing has to be completed, which is different for the two types of networks. Using this theory, the process of how to implement the networks in Matlab is explained. Different CNN:s are compared to each other, then the best performing CNN is compared to the LSTM-network. When comparing the two different networks to each other, cross validation is used to achieve the most correct result possible. The networks are compared by accuracy, least amount of training time and least amount of training data. A final resulti s presented, to show which type of network has the best performance, together with a discussion to explain the results. The CNN performed better than the LSTM-network in all aspects. A reflection on what could have been done differently to achieve a better result is posted.
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Thiyagaraja, Shanti. "Detection and Classification of Heart Sounds Using a Heart-Mobile Interface." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc1159216/.
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An early detection of heart disease can save lives, caution individuals and also help to determine the type of treatment to be given to the patients. The first test of diagnosing a heart disease is through auscultation - listening to the heart sounds. The interpretation of heart sounds is subjective and requires a professional skill to identify the abnormalities in these sounds. A medical practitioner uses a stethoscope to perform an initial screening by listening for irregular sounds from the patient's chest. Later, echocardiography and electrocardiography tests are taken for further diagnosis. However, these tests are expensive and require specialized technicians to operate. A simple and economical way is vital for monitoring in homecare or rural hospitals and urban clinics. This dissertation is focused on developing a patient-centered device for initial screening of the heart sounds that is both low cost and can be used by the users on themselves, and later share the readings with the healthcare providers. An innovative mobile health service platform is created for analyzing and classifying heart sounds. Certain properties of heart sounds have to be evaluated to identify the irregularities such as the number of heart beats and gallops, intensity, frequency, and duration. Since heart sounds are generated in low frequencies, human ears tend to miss certain sounds as the high frequency sounds mask the lower ones. Therefore, this dissertation provides a solution to process the heart sounds using several signal processing techniques, identifies the features in the heart sounds and finally classifies them. This dissertation enables remote patient monitoring through the integration of advanced wireless communications and a customized low-cost stethoscope. It also permits remote management of patients' cardiac status while maximizing patient mobility. The smartphone application facilities recording, processing, visualizing, listening, and classifying heart sounds. The application also generates an electronic medical record, which is encrypted using the efficient elliptic curve cryptography and sent to the cloud, facilitating access to physicians for further analysis. Thus, this dissertation results in a patient-centered device that is essential for initial screening of the heart sounds, and could be shared for further diagnosis with the medical care practitioners.
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Corona, Blanca Tovar. "Analysis and representation of heart sounds and murmurs." Thesis, University of Sussex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299958.
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Baranek, Humberto Leon. "Automatic detection and identification of cardiac sounds and murmurs." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63754.
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Marcus, Diveena Seshetta. "Sounds from the heart: Native American language and song." Thesis, Montana State University, 2011. http://etd.lib.montana.edu/etd/2011/marcus/MarcusD0511.pdf.
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Our world is witnessing the rapid extinction of indigenous cultures through colonization. This thesis is presented not to amplify decolonization but to honor the value and meaning of the oral society and its indigenous peoples through their culture's traditional and necessary components of language and song. The basis of this thesis pertains to the author's tribal relatives, the Coast Miwok original people of California known as Tamal Michchawmu which literally translates as the People of the West Coast. The author chooses to use this work as an advocacy for the worldview of indigenous peoples, particularly to matriarchal societies in which the Tamal Michchawmu are included. In this thesis, stories and interviews with scholars and with Native Americans studying their language and singing their songs as well as the author's personal experiences are included as support to the theory that language and song are formed from the foundation of a philosophy that is grounded within a peoples relationship with the land. My thesis question is: If this worldview is resurrected, how can it contribute to its indigenous people in a modern society?
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Tahmasbi, Mohammad Saeed. "VLSI implementation of heart sounds maximum entropy spectral estimation /." Title page, contents and summary only, 1994. http://web4.library.adelaide.edu.au/theses/09ENS/09enst128.pdf.
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Ewing, Gary John. "A new approacch to the analysis of the third heart sound." Title page, contents and summary only, 1988. http://web4.library.adelaide.edu.au/theses/09SM/09sme95.pdf.
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Feng, Shuo. "Designing for Stress Reduction by Connecting Heart Rate to Sounds." Thesis, KTH, Medieteknik och interaktionsdesign, MID, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191454.
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With the progress of society, an increasing number of people pay close attention to their health. In this study, we designed a Heart Rate based interactive sound to investigate how biodata-based interactive sounds can affect the well-being of people. We used a variety of approaches to analyzing the data and feedback from users. Firstly, the Trier Social Stress Test protocol was employed as a basis for the test. Also, a package of cultural probes such as photos, diaries and cards were used to collect data from users' everyday life. Recruited by using a snowball sampling technique, five users took and completed the test. From the analysis, we identified problems with our design and realized how to potentially improve the device in the future. The main conclusion that could be drawn was that Heart Rate-based interactive sounds can help users to reduce stress, but that most individuals were more willing to listen to steady sounds in order to relax.I takt med att samhället utvecklas, utvecklas också ett hälsomedvetet tänkande bland samhällets individer. I denna studie designade vi ett ljud baserad på hjärtfrekvens för att undersöka hur ljud baserade på biodata kan påverka välmåendet hos individer. Vi använde oss av en mängd tillvägagångssätt för att analysera data och återkopplingen från användarna. Det så kallade ”Trier Social Stress Test” protokollet utgjorde testets grund. Därtill användes en samling kulturella stimulis som exempelvis foton, dagböcker och kort, vilka användes för att samla data från användarnas vardagliga liv. Fem användare rekryterades genom snöbollsmetoden, och genomförde sedan testet. Utifrån analysen fann vi problem med vår design och insåg hur vi eventuellt kunde förbättra apparaten i framtiden. Den huvudsakliga slutsatsen som kan dras var att ljud baserad på hjärtfrekvens kan hjälpa användare att minska stress, fastän de flesta individer hellre ville lyssna på mer konstanta ljud för att slappna av.
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Gretzinger, David Theodor Kerr. "Analysis of heart sounds and murmurs by digital signal manipulation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ45444.pdf.
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Bentley, Paul Mark. "Time-frequency analysis of native and prosthetic heart valve sounds." Thesis, University of Edinburgh, 1996. http://hdl.handle.net/1842/10785.
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In the past, a number of researchers have applied various spectral estimation techniques in an attempt to analyse recorded heart sounds. The majority of these studies have used spectral estimation algorithms such as the Fourier transform and various autoregressive modelling techniques. Despite the definite potential these techniques have shown for the diagnosis of valvular heart disease, they are limited by their assumption of signal stationary and lack of relation to present stethoscope-based medical evaluation procedures. A solution to these limitations can be achieved by analysing the recorded sounds in the time-frequency domain rather than in the frequency-domain of time-domain independently. The research detailed in this thesis investigates the application of time-frequency techniques to the description and analysis of recorded heart sounds. Time-frequency is further investigated as a tool for the description of heart sounds in an attempt to diagnose valvular heart disease. Data used in the study was recorded from 100 subjects in four main valve populations. The four populations investigated were subjects with native heart valves, Carpentier-Edwards bioprosthetic heart valves, Bjork-Shiley metallic prosthetic heart valves and subjects before and after surgery for heart valve replacement. Prior to the analysis of these data sets, an investigation was performed into the suitability of various time-frequency techniques to the analysis of heart sounds. By comparing the short-time Fourier transform, wavelet transform, Wigner distribution and the Choi-Williams distribution it was found that the Choi-Williams distribution provides definite advantages over the other techniques due to its high resolution and reduced interference properties. Applying the Choi-Williams distribution to typical examples of each data set demonstrated that time-frequency offers definite potential as a heart sound descriptor. Typical results also demonstrate that time-frequency can be used as an aid to understanding the origins of heart sounds.
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Tinati, Mohammad Ali. "Time-frequency and time-scale analysis of phonocardiograms with coronary artery disease before and after angioplasty /." Title page, contents and abstract only, 1998. http://web4.library.adelaide.edu.au/theses/09PH/09pht587.pdf.
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Visagie, Claude. "Screening for abnormal heart sounds and murmurs by implementing neural networks." Thesis, Stellenbosch : University of Stellenbosch, 2007. http://hdl.handle.net/10019.1/3119.
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Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2007.This thesis is concerned with the testing of an “auscultation jacket” as a means of recording heart sounds and electrocardiography (ECG) data from patients. A classification system based on Neural Networks, that is able to discriminate between normal and abnormal heart sounds and murmurs, has also been developed . The classification system uses the recorded data as training and testing data. This classification system is proposed to serve as an aid to physicians in diagnosing patients with cardiac abnormalities. Seventeen normal participants and 14 participants that suffer from valve-related heart disease have been recorded with the jacket. The “auscultation jacket” shows great promise as a wearable health monitoring aid for application in rural areas and in the telemedicine industry. The Neural Network classification system is able to differentiate between normal and abnormal heart sounds with a sensitivity of 85.7% and a specificity of 94.1%.
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Bedi, Rajan. "Signal processing and frequency analysis of Carpentier-Edwards bioprosthetic heart valve sounds." Thesis, University of Edinburgh, 1994. http://hdl.handle.net/1842/10770.
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As a result of the inevitable patient risk associated with the Carpentier-Edwards bioprosthesis, reliable, periodic, post-operative evaluation of the integrity of the implanted valve is essential. The research detailed in this thesis proposes a method whereby diagnostic information concerning the functionality of the valve is extracted from the acoustic output produced by the operation of the prosthesis. This is achieved by analysing the spectral characteristics of the principal heart sound components contained within this acoustic signal. Results show that normally functioning, leaky and stiffening prostheses each exhibit unique spectral characteristics. Normally functioning aortic prostheses are characterised by four to five dominant frequency peaks, with the major concentration of spectral energy occurring in the region between 25Hz and 125Hz. Normally functioning mitral prostheses are characterised by two to three dominant peaks with the major concentration of spectral energy occurring in the region between d.c. and 100Hz. For leaky regurgitant bioprostheses and prostheses diagnosed as having stiffening calcified cusps, a shift was observed in spectral energy. For leaky mitral and aortic prostheses, the major distribution of spectral energy now occurs in the region between d.c. and 75Hz, whereas for stiffening aortic prostheses, the major concentration of spectral energy now occurs in the region between 50Hz and 200Hz. It was observed that the highest frequency which occurs at a level of -10dB below the maximum spectral response (0dB), may be used to discriminate between normally functioning, leaky and stiffening aortic prostheses, where mean frequencies for these conditions at the -10dB level were observed to be 113.6Hz, 53.7Hz and 238.1Hz respectively. A single discriminating parameter was not observed from the analysis of mitral sounds.
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Daura, Ashiru Sani. "A wavelet-based method for the classification of PCG signals." Thesis, University of Newcastle Upon Tyne, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244474.
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Romero-Vivas, Eduardo. "Hidden Markovian models applied to the analysis of heart sounds for diagnostic purposes." Thesis, University of Southampton, 2006. https://eprints.soton.ac.uk/425886/.
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Haghighi-Mood, Ali. "Analysis of phonocardiographic signals using advanced signal processing techniques." Thesis, University of Sussex, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321465.
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Vadali, Venkata Akshay Bhargav Krishna. "A Comparative Study of Signal Processing Methods for Fetal Phonocardiography Analysis." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7373.
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More than one million fetal deaths occur in the United States every year [1]. Monitoring the long-term heart rate variability provides a great amount of information about the fetal health condition which requires continuous monitoring of the fetal heart rate. All the existing technologies have either complex instrumentation or need a trained professional at all times or both. The existing technologies are proven to be impractical for continuous monitoring [2]. Hence, there is an increased interest towards noninvasive, continuous monitoring, and less expensive technologies like fetal phonocardiography.
Fetal Phonocardiography (FPCG) signal is obtained by placing an acoustic transducer on the abdomen of the mother. FPCG is rich in physiological bio-signals and can continuously monitor the fetal heart rate non-invasively. Despite its high diagnostic potential, it is still not being used as the secondary point of care. There are two challenges as to why it is still being considered as the secondary point of care; in the data acquisition system and the signal processing methodologies. The challenges pertaining to data acquisition systems are but not limited to sensor placement, maternal obesity and multiple heart rates. While, the challenges in the signal processing methodologies are dynamic nature of FPCG signal, multiple known and unknown signal components and SNR of the signal.
Hence, to improve the FPCG based care, challenges in FPCG signal processing methodologies have been addressed in this study. A comparative evaluation was presented on various advanced signal processing techniques to extract the bio-signals with fidelity. Advanced signal processing approaches, namely empirical mode decomposition, spectral subtraction, wavelet decomposition and adaptive filtering were used to extract the vital bio-signals. However, extracting these bio-signals with fidelity is a challenging task in the context of FPCG as all the bio signals and the unwanted artifacts overlap in both time and frequency. Additionally, the signal is corrupted by noise induced from the fetal and maternal movements as well the background and the sensor.
Empirical mode decomposition algorithm was efficient to denoise and extract the maternal and fetal heart sounds in a single step. Whereas, spectral subtraction was used to denoise the signal which was later subjected to wavelet decomposition to extract the signal of interest. On the other hand, adaptive filtering was used to estimate the fetal heart sound from a noisy FPCG where maternal heart sound was the reference input.
The extracted signals were validated by obtaining the frequency ranges computed by the Short Time Fourier Transform (STFT). It was observed that the bandwidths of extracted fetal heart sounds and maternal heart sounds were consistent with the existing gold standards. Furthermore, as a means of additional validation, the heart rates were calculated. Finally, the results obtained from all these methods were compared and contrasted qualitatively and quantitatively.
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Einstein, Daniel Richard. "Nonlinear acoustic analysis of the mitral valve /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/8064.
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Klavebäck, Kerstin. "A Rude Awakening to Sounds : A Study of the Soundscape in Joseph Conrad’s Heart of Darkness." Thesis, Högskolan i Halmstad, Sektionen för humaniora (HUM), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-23633.
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This study examines the significance of sounds and silence in Joseph Conrad’s novella Heart of Darkness (1902). The importance of visual effects has repeatedly been analyzed and therefore, it is high time to explore the text from an auditory perspective. By comparing and contrasting Victorian city sounds to sounds in the wilderness, I show that the urban and rural worlds have a great deal in common. Furthermore, by deconstructing the seemingly stable binary opposition of sound and silence as well as that of civilization and wilderness, it becomes evident that they are related and depend on one another. This paper also examines noise and how it is used as a means of power. Moreover, it deals with Thomas Edison’s invention, the phonograph, as an implicit discursive device in the text. In conclusion, it is argued that the sonic environment is of high significance and should therefore not be ignored and readers must try to close their eyes in order to hear what is said.
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Hudson, Erik Mark. "A Portable Computer System for Recording Heart Sounds and Data Modeling Using a Backpropagation Neural Network." UNF Digital Commons, 1995. http://digitalcommons.unf.edu/etd/158.
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Cardiac auscultation is the primary tool used by cardiologists to diagnose heart problems. Although effective, auscultation is limited by the effectiveness of human hearing. Digital sound technology and the pattern classification ability of neural networks may offer improvements in this area. Digital sound technology is now widely available on personal computers in the form of sound cards. A good deal of research over the last fifteen years has shown that neural networks can excel in diagnostic problem solving. To date, most research involving cardiology and neural networks has focussed on ECG pattern classification. This thesis explores the prospects of recording heart sounds in Wave format and extracting information from the Wave file for use with a backpropagation neural network in order to classify heart patterns.
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Tan, Zhen. "Low noise heart sound acquisition in wearable system for individual-centered CVD diagnosis." Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691773.
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Жемчужкіна, Т. В., and Т. В. Носова. "Сonstruction of phase portraits of PCG signals." Thesis, НТУ «ХПІ», 2021. https://openarchive.nure.ua/handle/document/17554.
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For PCG signals we constructed phase portraits (PP) in 2-dimensional state space. To demonstrate PP of heart sounds and murmurs we extracted main sounds from PCG signals. Different signals have different forms of PP and samples of main sounds can be separated from rest samples using PP. Showed applications of PP analysis. So, PP of PCG signals probably can be used for diagnostics of heart sounds and for segmentation of PCG signal without simultaneous ECG-recording.
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Gigstad, Lynda Lynell. "A comparison of an acoustic stethoscope and an amplified stethoscope in white noise and cafeteria noise during cardiac auscultation." PDXScholar, 1990. https://pdxscholar.library.pdx.edu/open_access_etds/3974.
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A basic relationship between stethoscopic auscultation and background noise interference was reviewed and examined in this study. The principle experimental design of the study questioned whether hospital background noise levels are capable of masking the threshold of detection for auscultated heart sounds. Several cited studies monitoring background noise levels in various hospital locations have reported averages exceeding the U.S. Environmental Protection Agency (EPA) (1974) and World Health Organization (WHO) (1980) recommendations of "quiet", namely 35 to 40 dBA (Falk & Woods, 1973; Hilton, 1985, 1987; Shapiro & Berland, 1972; Turner, et al., 1975; Woods & Falk, 1974) by as much as 46 to 51 dB, i.e., up to 86 dBA (Shapiro & Berland 1972). In addition to the previous query, a review of the literature reflected a lack of implementatory standards regarding the acoustic stethoscopic output and the masking effects of noise during the auscultation process. Specifically, this study ascertained the effective masking level (EML) intensities of two noise environments, white noise and cafeteria noise, for cardiac auscultation through an acoustic stethoscope and an amplified stethoscope. Two principle measurements were employed in the experimental protocol: an objective measurement employing a method of adjustment detection identification task of the EML, and subjective responses solicited by a forced-choice questionnaire. Sixteen normal hearing listener's were selected to participate in the experiment. Objective measures were analyzed using a MANOVA and a Pearson Product Moment Coefficient of correlation. The subjective questionnaire data were analyzed with a two-tailed T-test. All analyses were based on a .05 level of confidence.
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Koegelenberg, Suretha. "Application of laser doppler vibrocardiography for human heart auscultation." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86649.
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Thesis (MScEng)--Stellenbosch University, 2014.ENGLISH ABSTRACT: This thesis investigates the feasibility of the laser Doppler vibrometer (LDV) for use in the autonomous auscultation of the human heart. As a non-contact measurement device, the LDV could become a very versatile biomedical sensor. LDV, stethoscope, piezoelectric accelerometer (PA) and electrocardiogram (ECG) signals were simultaneously recorded from 20 volunteers at Tygerberg Hospital. Of the 20 volunteers, 17 were confirmed to have cardiovascular disease. 3 patients with normal heart sounds were recorded for control data. The recorded data was successfully denoised using soft threshold wavelet denoising and ensemble empirical mode decomposition. The LDV was compared to the PA in common biomedical applications and found to be equally accurate. The heart sound cycles for each participant were segmented using a combination of ECG data and a simplicity curve. Frequency domain features were extracted from each heart cycle and input into a k-nearest neighbours classifier. It was concluded that the LDV can form part of an autonomous, non-contact auscultation system.
AFRIKAANSE OPSOMMING: Hierdie tesis ondersoek die haalbaarheid daarvan om die laser Doppler vibrasiemeter (LDV) vir die outonome beluistering van die menslike hart te gebruik. As 'n kontaklose meettoestel kan die LDV werklik 'n veelsydige biomediese sensor word. Twintig vrywilligers by die Tygerberg Hospitaal se LDV-, stetoskoop-, piësoelektriese versnellingsmeter (PV)- en elektrokardiogram (EKG) seine is gelyktydig opgeneem. Uit die 20 vrywilligers was daar 17 bevestigde gevalle van kardiovaskulêre siektes. Die data van drie pasiënte met normale hartklanke is as kontroledata opgeneem. Geraas is suksesvol uit die opgeneemde data verwyder deur 'n kombinasie van sagtedrempelgolf en saamgestelde empiriese modus ontladingstegnieke. Die LDV was vergelyk met die PV vir algemene biomediese gebruike en daar was gevind dat dit vergelykbare akkuraatheid het. Die hartklanksiklusse van elke deelnemer is gesegmenteer deur EKG data en 'n eenvoudskromme te kombineer. Frekwensiegebiedskenmerke is uit elke hartsiklus onttrek en in 'n k-naastebuurpunt klassifiseerder ingevoer. Daar is tot die gevolgtrekking gekom dat die LDV deel van 'n outonome, kontaklose beluisteringstelsel kan uitmaak.
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De, Vos Jacques Pinard. "Automated pediatric cardiac auscultation." Thesis, Link to the online version, 2005. http://hdl.handle.net/10019/1008.
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Brites, Ivo Sérgio Guimarães [UNESP]. "Análise de bulhas cardíacas usando wavelets visando auxiliar no diagnóstico médico." Universidade Estadual Paulista (UNESP), 2014. http://hdl.handle.net/11449/111108.
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000796411.pdf: 2346587 bytes, checksum: 4c090312f84027a406b4735ddd531092 (MD5)A presente dissertação teve como objetivo apresentar uma proposta de análise de bulhas cardíacas (sons produzidos pelo fechamento das válvulas do coração) usando Transformada Discreta de Wavelet. Neste trabalho as bulhas cardíacas, gravadas em um arquivo digital, foram processadas através da Transformada Discreta de Wavelet nível 6 da db7 e da db6 de Daubechies e feita uma análise de sua média e do seu desvio padrão. Com a métrica desvio padrão aplicada ao sexto nível da db6 de Daubechies para classificação de sinais normais e anormais em um banco de dados de 70 amostras obteve-se um acerto da ordem de 95,71%
This dissertation aims to present a proposal for interpretation of heart sounds using Discrete Wavelet Transform. The heart sounds recorded in a digital file were processed using level 6 of db7 and level 6 of db6 Daubechies Discrete Wavelet Transform and extracting the media and standard deviation features. The standard deviation of level6 of db6 Daubechies Discrete Wavelet is are able to differentiate between normal and abnormal from database of 70 heart sound signals with 95.71% of correct classifications
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Brites, Ivo Sérgio Guimarães. "Análise de bulhas cardíacas usando wavelets visando auxiliar no diagnóstico médico /." Ilha Solteira, 2014. http://hdl.handle.net/11449/111108.
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Orientador: Nobuo OkiBanca: Suely Cunha Amaro Mantovani
Banca: Carlos Aurélio Faria da Rocha
Resumo: A presente dissertação teve como objetivo apresentar uma proposta de análise de bulhas cardíacas (sons produzidos pelo fechamento das válvulas do coração) usando Transformada Discreta de Wavelet. Neste trabalho as bulhas cardíacas, gravadas em um arquivo digital, foram processadas através da Transformada Discreta de Wavelet nível 6 da db7 e da db6 de Daubechies e feita uma análise de sua média e do seu desvio padrão. Com a métrica desvio padrão aplicada ao sexto nível da db6 de Daubechies para classificação de sinais normais e anormais em um banco de dados de 70 amostras obteve-se um acerto da ordem de 95,71%
Abstract: This dissertation aims to present a proposal for interpretation of heart sounds using Discrete Wavelet Transform. The heart sounds recorded in a digital file were processed using level 6 of db7 and level 6 of db6 Daubechies Discrete Wavelet Transform and extracting the media and standard deviation features. The standard deviation of level6 of db6 Daubechies Discrete Wavelet is are able to differentiate between normal and abnormal from database of 70 heart sound signals with 95.71% of correct classifications
Mestre
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Spadaccini, Andrea. "Innovative Traits, Algorithms and Application Scenarios for Mono-multimodal Biometric Recognition." Doctoral thesis, Università di Catania, 2012. http://hdl.handle.net/10761/1096.
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Identity verification is one of the most common and important processes in our daily lives. For centuries, humans have relied on the visual appearance of their peers - or other distinctive traits - to recognize them.
Currently, most of the traditional authentication methods infer one s identity by either verifying the knowledge of a shared secret (i.e., password) or the possession of a given object (i.e., token); both methods are sub-optimal, since they do not directly verify the person s identity, but an alternate and less
rich representation that could also very easily stolen or inadvertently shared.
Biometrics offers a natural solution to this problem, by providing quantitative methods for recognizing one s identity by the analysis of either physiological or behavioural traits.
In addition to the traditional biometric traits, such as fingerprint, iris or voice, there is a growing interest in novel biometric traits, that can be used in conjunction with the most established ones to compensate to their weaknesses. In the first part of this thesis, we will analyze the usage of heart sounds as a physiological trait for biometric recognition, discussing some novel ad-hoc algorithms developed to process them.
Forensic analysts often have to determine whether a given speech sample was uttered by a suspect or not; in the second part of the thesis, we will investigate the usage of automatic text-independent speaker recognition systems in this context, exploring the limits of this approach and proposing new
solutions.
Finally, given the capillary diffusion that Internet access has gained in the last years, we will analyze the problem of biometric authentication for web application. Through the performance analysis of 3 biometric systems and their combination using 2 multi-biometric score level fusion strategies, we will find the optimal combination of those system; we will then present the architecture and implementation of an open-source web-based multi-biometric authentication system based on speech and face recognition, fused together
using the optimal strategy identified in the preliminary analysis phase.
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Tran, Merry Thi. "Applications of Digital Signal Processing with Cardiac Pacemakers." PDXScholar, 1992. https://pdxscholar.library.pdx.edu/open_access_etds/4582.
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Because the voltage amplitude of a heart beat is small compared to the amplitude of exponential noise, pacemakers have difficulty registering the responding heart beat immediately after a pacing pulse. This thesis investigates use of digital filters, an inverse filter and a lowpass filter, to eliminate the effects of exponential noise following a pace pulse. The goal was to create a filter which makes recognition of a haversine wave less dependent on natural subsidence of exponential noise. Research included the design of heart system, pacemaker, pulse generation, and D sensor system simulations. The simulation model includes the following components: \ • Signal source, A MA TLAB generated combination of a haversine signal, exponential noise, and myopotential noise. The haversine signal is a test signal used to simulate the QRS complex which is normally recorded on an ECG trace as a representa tion of heart function. The amplitude is approximately 10 mV. Simulated myopotential noise represents a uniformly distributed random noise which is generated by skeletal muscle tissue. The myopotential noise has a frequency spectrum extending from 70 to 1000Hz. The amplitude varies from 2 to 5 mV. Simulated exponential noise represents the depolarization effects of a pacing pulse as seen at the active cardiac lead. The amplitude is about -1 volt, large in comparison with the haversine signal. • AID converter, A combination of sample & hold and quantizer functions translate the analog signal into a digital signal. Additionally, random noise is created during quantization. • Digital filters, An inverse filter removes the exponential noise, and a lowpass filter removes myopotential noise. • Threshold level detector, A function which detects the strength and amplitude of the output signal was created for robustness and as a data sampling device. The simulation program is written for operation in a DOS environment. The program generates a haversine signal, myopotential noise (random noise), and exponential noise. The signals are amplified and sent to an AID converter stage. The resultant digital signal is sent to a series of digital filters, where exponential noise is removed by an inverse digital filter, and myopotential noise is removed by the Chebyshev type I lowpass digital filter. The output signal is "detected" if its waveform exceeds the noise threshold level. To determine what kind of digital filter would remove exponential noise, the spectrum of exponential noise relative to a haversine signal was examined. The spectrum of the exponential noise is continuous because the pace pulse is considered a non-periodic signal (assuming the haversine signal occurs immediately after a pace pulse). The spectrum of the haversine is also continuous, existing at every value of frequency co. The spectrum of the haversine is overlapped by the spectrum of and amplitude of the exponential, which is several orders of magnitude larger. The exponential cannot be removed by conventional filters. Therefore, an inverse filter approach is used to remove exponential noise. The transfer function of the inverse filter of the model has only zeros. This type of filter is called FIR, all-zero, non recursive, or moving average. Tests were run using the model to investigate the behavior of the inverse filter. It was found that the haversine signal could be clearly detected within a 5% change in the time constant of the exponential noise. Between 5% and 15% of change in the time constant, the filtered exponential amplitude swamps the haversine signal. The sensitivity of the inverse filter was also studied: when using a fixed exponential time constant but changing the location of the transfer function, the effect of the exponential noise on the haversine is minimal when zeros are located between 0.75 and 0.85 of the unit circle. After the source signal passes the inverse filter, the signal consists only of the haversine signal, myopotential noise, and some random noise introduced during quantization. To remove these noises, a Chebyshev type I lowpass filter is used.
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Minardi, Gabriele. "Progettazione e sviluppo di un prototipo di dispositivo wearable per il monitoraggio dell'attivita elettro-meccanica del cuore." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7898/.
Full textAbstract:
Il presente lavoro di tesi è finalizzato allo sviluppo di un dispositivo indossabile, e minimamente invasivo, in grado di registrare in maniera continua segnali legati all’attività elettromeccanica del muscolo cardiaco, al fine di rilevare eventuali anomalie cardiache.
In tal senso il sistema non si limita alla sola acquisizione di un segnale ECG, ma è in grado di rilevare anche i toni cardiaci, ovvero le vibrazioni generate dalla chiusura delle valvole cardiache, la cui ampiezza è espressione della forza contrattile (funzione meccanica) del cuore. Il presente lavoro di tesi ha riguardato sia la progettazione che la realizzazione di un prototipo di tale dispositivo ed è stato svolto presso il laboratorio di Bioingegneria del Dipartimento di Medicina Specialistica Diagnostica e Sperimentale dell’Università di Bologna, sito presso l’Azienda Ospedaliero-Universitaria Policlinico Sant’Orsola-Malpighi. Il sistema finale consiste in un dispositivo applicabile al torace che, attraverso una serie di sensori, è in grado di rilevare dati legati alla meccanica del cuore (toni cardiaci), dati elettrici cardiaci (ECG) e dati accelerometrici di attività fisica. Nello specifico, il sensing dei toni cardiaci avviene attraverso un accelerometro in grado di misurare le vibrazioni trasmesse al torace. I tracciati, raccolti con l’ausilio di una piattaforma Arduino, vengono inviati, tramite tecnologia Bluetooth, ad un PC che, attraverso un applicativo software sviluppato in LabVIEW™, ne effettua l’analisi, il salvataggio e l’elaborazione in real-time, permettendo un monitoraggio wireless ed in tempo reale dello stato del paziente.
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Sedighian, Pouye. "Pediatric heart sound segmentation." Thesis, California State University, Long Beach, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1526952.
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Recent advances in technology have facilitated the prospect of automatic cardiac auscultation by using digital stethoscopes. This in turn creates the need for development of algorithms capable of automatic segmentation of the heart sound. Pediatric heart sound segmentation is a challenging task due to various factors including the significant influence of respiration on the heart sound. This project studies the application of homomorphic filtering and Hidden Markov Model for the purpose of pediatric heart sound segmentation. The efficacy of the proposed method is evaluated on a publicly available dataset and its performance is compared with those of three other existing methods. The results show that our proposed method achieves accuracy of 92.4% ±1.1% and 93.5% ±1.1% in identification of first and second heart sound components, and is superior to four other existing methods in term of accuracy or time complexity.
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Chitnis, Anurag Ashok. "Mobile-Based Smart Auscultation." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1011820/.
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In developing countries, acute respiratory infections (ARIs) are responsible for two million deaths per year. Most victims are children who are less than 5 years old. Pneumonia kills 5000 children per day. The statistics for cardiovascular diseases (CVDs) are even more alarming. According to a 2009 report from the World Health Organization (WHO), CVDs kill 17 million people per year. In many resource-poor parts of the world such as India and China, many people are unable to access cardiologists, pulmonologists, and other specialists. Hence, low skilled health professionals are responsible for screening people for ARIs and CVDs in these areas. For example, in the rural areas of the Philippines, there is only one doctor for every 10,000 people. By contrast, the United States has one doctor for every 500 Americans. Due to advances in technology, it is now possible to use a smartphone for audio recording, signal processing, and machine learning. In my thesis, I have developed an Android application named Smart Auscultation. Auscultation is a process in which physicians listen to heart and lung sounds to diagnose disorders. Cardiologists spend years mastering this skill. The Smart Auscultation application is capable of recording and classifying heart sounds, and can be used by public or clinical health workers. This application can detect abnormal heart sounds with up to 92-98% accuracy. In addition, the application can record, but not yet classify, lung sounds. This application will be able to help save thousands of lives by allowing anyone to identify abnormal heart and lung sounds.
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Soukup, Ladislav. "Vyhodnocení srdečního výdeje bioimpedanční metodou u pacientů se stimulátorem." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219749.
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This thesis deals with the possibility of using impedance cardiography for calculating cardiac output. Kubicek’s, Sramek‘s and Sramek-Bernstein‘s methods are discussed here. These methods were applied to a data set, obtained by measuring on subjects with implanted cardiostimulators. The subjects’ heart rate was being changed by the programing of cardiostimulators. Thanks to this procedure the measured data were not affected by artifacts, connected with the heart rate change caused by a body stress, or other influences. An influence of heart rate on a cardiac output value based on the statistical processing of the data set was studied.
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Wong, Spencer Geng. "DESIGN, CHARACTERIZATION AND APPLICATION OF A MULTIPLE INPUT STETHOSCOPE APPARATUS." DigitalCommons@CalPoly, 2014. https://digitalcommons.calpoly.edu/theses/1307.
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For this project, the design, implementation, characterization, calibration and possible applications of a multiple transducer stethoscope apparatus were investigated. The multi-transducer sensor array design consists of five standard stethoscope diaphragms mounted to a rigid frame for a-priori knowledge of their relative spatial locations in the x-y plane, with compliant z-direction positioning to ensure good contact and pressure against the subject’s skin for reliable acoustic coupling. When this apparatus is properly placed on the body, it can digitally capture the same important body sounds investigated with standard acoustic stethoscopes; especially heart sounds. Acoustic signal inputs from each diaphragm are converted to electrical signals through microphone pickups installed in the stethoscope connective tubing; and are subsequently sampled and digitized for analysis. With this system, we are able to simultaneously interrogate internal body sounds at a sampling rate of 2 KHz, as most heart sounds of interest occur below 200 Hz.
This system was characterized and calibrated by chirp and impulse signal tests. After calibrating the system, a variety of methods for combining the individual sensor channel data to improve the detectability of different signals of interest were explored using variable-delay beam forming. S1 and S2 heart sound recognition with optimized beam forming delays and inter-symbol noise elimination were investigated for improved discernment of the S1 or S2 heart sounds by a user. Also, stereophonic presentation of heart sounds was also produced to allow future investigation of its potential clinical diagnostic efficacy.
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Mgdob, Hosam Mohamed. "Heart sound acquisition system and signal analysis." Thesis, University of Sussex, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400032.
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Hebden, John Edward. "Acquisition and analysis of heart sound data." Thesis, University of Sussex, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.360518.
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Hedayioglu, Fabio de Lima. "Heart Sound Segmentation for digital stethoscope integration." Master's thesis, Faculdade de Medicina da Universidade do Porto, 2009. http://hdl.handle.net/10216/22169.
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Hedayioglu, Fabio de Lima. "Heart Sound Segmentation for digital stethoscope integration." Dissertação, Faculdade de Medicina da Universidade do Porto, 2009. http://hdl.handle.net/10216/22169.
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Horton, Willie Charles Jr. "Armed With A Heart." ScholarWorks@UNO, 2009. http://scholarworks.uno.edu/td/1007.
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This paper thoroughly examines the production of the thesis short film, Armed With A Heart, from conception to completion. Each area of the film's production is carefully dissected, including the writing, production design, cinematography, editing, sound, technology, workflow, and direction. Each of these areas contain a myriad of decisions that were made in effort to fulfill the overall vision of the movie as being a character driven, psychological thriller produced with a high production value. The aforementioned decisions are discussed at length. Documented feedback from test audiences is also reviewed in an attempt to objectively critique the final film.
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Dennis, Aaron W. "Noninvasive estimation of pulmonary artery pressure using heart sound analysis /." Diss., CLICK HERE for online access, 2010. http://contentdm.lib.byu.edu/ETD/image/etd3329.pdf.
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Dennis, Aaron W. "Noninvasive Estimation of Pulmonary Artery Pressure Using Heart Sound Analysis." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/1971.
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Right-heart catheterization is the most accurate method for estimating pulmonary artery pressure (PAP). Because it is an invasive procedure it is expensive, exposes patients to the risk of infection, and is not suited for long-term monitoring situations. Medical researchers have shown that PAP influences the characteristics of heart sounds. This suggests that heart sound analysis is a potential noninvasive solution to the PAP estimation problem. This thesis describes the development of a prototype system, called PAPEr, which estimates PAP noninvasively using heart sound analysis. PAPEr uses patient data with machine learning algorithms to build models of how PAP affects heart sounds. Data from 20 patients was used to build the models and data from another 31 patients was used as a validation set. PAPEr diagnosed these 31 patients for pulmonary hypertension with an accuracy of 77 percent.
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Lu, Ling-Pei. "Sound at heart and right in hand Mobile's road to secession /." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Spring/doctoral/LU_LING_5.pdf.
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Li, Xiang Fei. "Time-frequency analysis of heart sound signal based on unwinding AFD." Thesis, University of Macau, 2015. http://umaclib3.umac.mo/record=b3335800.
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da, Cunha Daise Nunes Queiroz. "Properties of Flow Through the Ascending Aorta in Boxer Dogs with Mild Aortic Stenosis: Momentum, Energy, Reynolds Number, Womersley’s, Unsteadiness Parameter, Vortex Shedding, and Transfer Function of Oscillations from Aorta to Thoracic Wall." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1243910694.
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Zeng, Ke Han. "Innovative cuboid method to attenuate noises from site-measured heart sound signals." Thesis, University of Macau, 2015. http://umaclib3.umac.mo/record=b3335275.
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Swick, Julie Burkey. "A study to investigate the mathematical relationships between the frequency composition of the first heart sound and the force generating capability of the heart." Connect to this title online, 1987. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1102102077.
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Shiu, Shr-ting, and 許時挺. "Reducing heart sound interference from lung sounds by Hilbert-Huang transform." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/33285381065777052430.
Full textAbstract:
碩士國立中央大學
電機工程研究所
100
In this research, we take heart sound signals as interference to lung sounds and propose a method to reduce the interfering heart sounds in lung sounds. The lung sounds were obtained by placing an electronic stethoscope head on the chest of the subject and recording the output signal of the microphone in the stethoscope head. We incorporated Hilbert-Huang Transform (HHT) in our heart sound reduction. HHT was proposed by Norden E. Huang. It is especially suitable for processing non-stationary and non-linear signals, such as physiological signals. In HHT, the target signal can be decomposed into a number of intrinsic mode functions (IMFs) by empirical mode decomposition (EMD).These IMFs can be transformed into the Hilbert space, and then their instantaneous frequencies can be observed in the time domain. The performance of our heart sound reduction algorithm was evaluated in terms of the heart-sound-noise reduction percentage (HNRP), which .is about 80% in our experiments. This result is comparatively better than that of a wavelet-based method shown in the literature.
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"A new stethoscope for reduction of heart sounds from lung sound recordings." 2001. http://library.cuhk.edu.hk/record=b5890844.
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Yip Lung.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.
Includes bibliographical references.
Abstracts in English and Chinese.
Chapter 1 --- Introduction
Chapter 1.1 --- Heart and Lung Diseases --- p.1
Chapter 1.1.1 --- Hong Kong --- p.1
Chapter 1.1.2 --- China --- p.2
Chapter 1.1.3 --- the United States of America (USA) --- p.3
Chapter 1.2 --- Auscultation --- p.3
Chapter 1.2.1 --- Introduction of Auscultation --- p.4
Chapter 1.2.2 --- Comparison between Auscultation and Ultrasound --- p.6
Chapter 1.3 --- Stethoscope --- p.7
Chapter 1.3.1 --- History of Stethoscope --- p.7
Chapter 1.3.2 --- New Electronic Stethoscope --- p.14
Chapter 1.4 --- Main Purpose of the Study --- p.16
Chapter 1.5 --- Organization of Thesis --- p.16
References --- p.18
Chapter 2 --- A New Electronic Stethoscope's Head
Chapter 2.1 --- Introduction --- p.20
Chapter 2.2 --- Biopotential Electrode --- p.21
Chapter 2.2.1 --- Flexible Electrode --- p.21
Chapter 2.2.2 --- Laplacian Electrocardiogram --- p.22
Chapter 2.3 --- Transducer --- p.25
Chapter 2.4 --- Design of the Head of Stethoscope --- p.26
Chapter 2.5 --- Experimental Results --- p.27
Chapter 2.5.1 --- Bias Voltage of Condenser Microphone --- p.27
Chapter 2.5.2 --- Frequency Response of New Stethoscope's Head --- p.29
Chapter 2.6 --- Discussion --- p.30
Chapter 2.7 --- Section Summary --- p.31
References --- p.33
Chapter 3 --- Signal Pre-processing Unit
Chapter 3.1 --- Introduction --- p.35
Chapter 3.2 --- High Input Impedance IC Amplifier --- p.36
Chapter 3.3 --- Voltage Control Voltage Source High Pass Filter Circuit --- p.37
Chapter 3.4 --- Multiple Feed Back Low Pass Filter Circuit --- p.39
Chapter 3.5 --- Overall Circuit --- p.41
Chapter 3.6 --- Experimental Results --- p.43
Chapter 3.7 --- Discussion --- p.46
Chapter 3.8 --- Section Summary --- p.47
References --- p.48
Chapter 4 --- Central Platform
Chapter 4.1 --- Introduction --- p.49
Chapter 4.2 --- Adaptive Filter --- p.49
Chapter 4.2.1 --- Introduction to Adaptive Filtering --- p.49
Chapter 4.2.2 --- Least-Mean-Square (LMS) Algorithm --- p.51
Chapter 4.2.3 --- Applications --- p.52
Chapter 4.3 --- Offline Processing --- p.54
Chapter 4.3.1 --- WINDAQ and MATLAB --- p.55
Chapter 4.3.2 --- Direct Reference Algorithm --- p.57
Chapter 4.3.3 --- Determination of Parameters in DRA --- p.62
Chapter 4.3.4 --- Experimental Results of DRA --- p.67
Chapter 4.3.5 --- Acoustic Waveform Based Algorithm --- p.72
Chapter 4.3.6 --- Experimental Results of AWBA --- p.81
Chapter 4.4 --- Online Processing --- p.85
Chapter 4.4.1 --- LABVIEW --- p.85
Chapter 4.4.2 --- Automated Gain Control --- p.88
Chapter 4.4.3 --- Implementation of LMS adaptive filter --- p.89
Chapter 4.4.4 --- Experimental Results of Online-AGC --- p.92
Chapter 4.5 --- Discussion --- p.93
Chapter 4.6 --- Section Summary --- p.97
References --- p.98
Chapter 5 --- Conclusion and Further Development
Chapter 5.1 --- Conclusion of the Main Contribution --- p.100
Chapter 5.2 --- Future Works --- p.102
Chapter 5.2.1 --- Modification of the Head of Stethoscope --- p.102
Chapter 5.2.2 --- Validation of Abnormal Breath --- p.102
Chapter 5.2.3 --- Low Frequency Analysis --- p.102
Chapter 5.2.4 --- AGC-AWBA Approach --- p.102
Chapter 5.2.5 --- Standalone Device --- p.103
Chapter 5.2.6 --- Demand on Stethoscope --- p.109
References --- p.110
Appendix
Chapter A.1 --- Determination of parameters in VCVS High Pass Filter --- p.106
Chapter A.2 --- Determination of parameters in MFB Low Pass Filter --- p.110
Chapter A.3 --- Source code of DRA (MATLAB) --- p.114
Chapter A.4 --- Source code of AWBA (MATLAB) --- p.129
Chapter A.5 --- Source code of online AGC (LABVIEW) --- p.134
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Tseng, Yi-Li, and 曾乙立. "Early Detection of Ischemic Heart Disease Using Multi-lead ECG and Heart Sounds." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/87080356466389715644.
Full textAbstract:
博士國立臺灣大學
醫學工程學研究所
100
Ischemic heart disease has become the first place of ten leading causes of death for many years. According to the statistic results from WHO, up to 16% of mortality is due to ischemic heart disease. The main reason of high death rate is its lack of early symptoms. Patients suffer from sudden death only after a short period of the occurring of acute coronary syndromes. Some even die without any early symptoms. Therefore, early detection of myocardial ischemia has become an important issue recently. In this study, we implemented a non-invasive 12-lead electrocardiogram (ECG) and a phonocardiogram (PCG) monitoring system, and high-accuracy analyzing methods are also proposed for the early detection of ischemic heart diseases. By the detection of the ischemia of cardiac muscles in its early stage, ischemic heart disease can be detected before the occurring of acute symptoms. Myocardial ischemia commonly manifests as ST- and T-wave changes on the ECG, or the third heart sound (S3) and the fourth heart sound (S4) of the PCG. For the analysis of ECG signals, we proposed two methods, support vector machine (SVM) and sparse representation-based classification (SRC), to detect abnormal ST-T complex. It integrates knowledge-based and novel classifying methods to extract essential information from ECG signals. In comparison with previous methods, the sensitivity for detecting myocardial ischemia is greatly improved using our methods. For the detection of S3 and S4, a time-frequency analysis method, Hilbert-Huang transform (HHT), was used to analyze non-linear and non-stationary PCG signals. This method can decompose the signal adaptively and acquire the instantaneous frequency. Therefore, all the abnormal components of PCG signals correlated to myocardial dysfunction can be detected simultaneously. The design of the monitoring of these non-invasive signals is based on remote home health care concepts. The recording of 12-lead ECG is designed using multiplexing technique suitable for wireless transmission. Moreover, the design of the electronic stethoscope is based on medical concepts with modulated equalizer. In this investigation, both analyzing methods and monitoring systems for 12-lead ECG and heart sound are proposed. The sensitivity and accuracy of the proposed methods are of better performance compared to previous methods. Furthermore, the whole monitoring system is aimed for remote home health care. With these concepts, detection of myocardial ischemia in its early stage using non-invasive home health care system could be feasible.