The purpose of this study was to compare the heart rates of dogs presenting with spontaneous atrial fibrillation (AF) by a surface electrocardiogram (ECG) and a 24 hour ambulatory ECG (Holter recording) in order to determine if there was a difference between these two diagnostic tests. Seven dogs with clinically stable, spontaneous AF were evaluated with a 6 lead surface ECG (MAC 5000, GE® Milwaukee) and a Holter monitor (Monitor device: LifecardCE Delmar Reynolds Medical, Holter analysis:Aria Holter software). Statistical analyses, including t-tests and linear regression models, were performed using Stata® data-analysis and statistical software. When heart rates (bpm) determined by both diagnostic testing methods were compared individually and among all of the dogs, no statistically significant differences were found. Complete data for analysis were available in 4 of the 7 dogs. This study demonstrates that despite the potential superiority of Holter monitoring relative to the surface ECG for the diagnosis of cardiac arrhythmias, average heart rates were not statistically different in these 4 dogs with controlled AF. Therefore, the average HR determined by surface ECG in the hospital may be as reliable as the average HR determined by Holter monitoring in dogs with well controlled spontaneous AF.

In the thesis, we study the data collected from VICU of Kaohsiung Veterans General Hospital.The data consists of the following two kinds. The data of the first kind is ten minute ECG data with sampling frequency 500Hz. The data of the second kind is long term one minute average heart rate. There are two main topics studies in this thesis. In the first part, we consider the standard deviations which be taked log and medians of RR intervals, PR intervals and RT intervals, respectively derived from first kind data. By considering the odds ratio¡Bsensitivity and specificity, and we select the heart classification vectors. The object is to classify among normal and ventricular heart disease (VSD), normal and ventricular heart disease with congestive heart failure (VSD+CHF). We proposed a method of both variables and two-step classification procedure. Furthermore, we built the logistic regression models. In the second part, we derive the distribution of the spectrum power ratio of low frequency to high frequency. Shewhart control chart and Tabular cusum chart are constructed to monitor RG. Also, we discover the periodicity of RG. Finally, there exists positive correlation between RA¡]or RG¡^ and autocorrelation of lag one of RR interval.

In this thesis, a low-power current-mode instrumentation amplifier is proposed for the portable physiological signal recording system. This proposed instrumentation amplifier is used as a front-end amplifier of physiological signal recording system. In general, the physiological signal is very small, for example, the electrocardiogram (ECG) signals. Therefore, the system needs a front-end amplifier to amplify small physiological signals so that it is easier to analyze the signals. Besides, the system will be operated for a longer period because of the proposed amplifier¡¦s low-power property. The circuit theorem, design process and simulation, circuit layout as well as the measurement results all have detailed description in this study. Moreover, a specific physiological signal recording system prototype is proposed. This proposed instrumentation amplifier has used TSMC 0.35 £gm 2P4M CMOS process technology.

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No / Introduction There is increasing evidence that lowering HR in cardiovascular disease may be beneficial. Recent trials have documented heart rate (HR) using supine ECG and the NICE guideline for heart failure[1,2] suggests lowering HR below 75 bpm but without specifying how HR should be measured. There is no published data on how HR measured by supine ECG compares to “real world” measurement in the clinic or surgery and any discrepancy might lead to overzealous introduction of HR lowering treatment. Method HR was measured in 136 consecutive patients attending a new cardiology OP clinic. Three methods of measuring HR were compared in the following sequence: Supine HR measured by ECG “real world” measurement by the nurse using Dynamat (auto) Manually over 30 sec during examination (Dr). Patients with dysrhythmia were excluded. Findings HR measured using these 3 methods has been presented separately and has shown a significant difference with ECG HR slower on average by >6bpm vs. either auto or Dr Measurement. The table shows the number and % of patients where HR was either ≥ 70bpm (Shift evidence) or ≥ 75 bpm (Nice guidelines) measured by one or two methods but not all three. Conclusion Real world HR measurement is consistently higher than supine ECG HR and may therefore lead to over inclusive treatment according to guideline recommendations. The method used to measure HR should be defined both in clinical trials and in published guidelines. Supine ECG is suggested as the preferred method for documenting HR prior to initiating rate lowering therapy.

Submitted by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-03-17T10:07:43Z No. of bitstreams: 2 Dissertação - Francisco P. Romero.pdf: 7624666 bytes, checksum: 863de5e0a188b3c163dd2ba3c0533962 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-03-17T10:07:59Z (GMT) No. of bitstreams: 2 Dissertação - Francisco P. Romero.pdf: 7624666 bytes, checksum: 863de5e0a188b3c163dd2ba3c0533962 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-03-17T10:08:34Z (GMT) No. of bitstreams: 2 Dissertação - Francisco P. Romero.pdf: 7624666 bytes, checksum: 863de5e0a188b3c163dd2ba3c0533962 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-03-17T10:08:34Z (GMT). No. of bitstreams: 2 Dissertação - Francisco P. Romero.pdf: 7624666 bytes, checksum: 863de5e0a188b3c163dd2ba3c0533962 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-12-20 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Cardiovascular diseases are the leading cause of death worldwide, accounting for 17.3 million deaths per year. The electrocardiogram (ECG) is a non-invasive technique widely used for the detection of cardiac diseases. To increase diagnostic sensitivity, ECG is acquired during exercise stress tests or in ambulatory way. Under these acquisition conditions the ECG is strongly affected by some types of noise, mainly by baseline (BL) wander. Currently in the literature, there are several methods for the elimination of BL, but no comparative study has been found that quantitatively evaluates these methods using the same signals. In this work a spectral characterization of the BL was made where it has been proven that these contain spectral components up to 3.14 Hz which exceeds the values established by the American Heart Association. We also implemented nine methods for the elimination of BL, which are interpolation using cubic splines, FIR filtering, IIR filtering, LMS adaptive filtering, moving average filter, independent component analysis, interpolation and successive median subtractions, decomposition in empirical modes and wavelet filtering. They were evaluated qualitatively and quantitatively. For the quantitative evaluation, the following similarity metrics were used: absolute maximum distance, sum of squares of distances and percentage of mean square error distance. Several experiments were performed using synthetic ECG signals, real QT Database ECG, artificial and real BL noises from the Noise Stress Test Database. The best results were obtained by the method based on FIR high pass filtering with cutoff frequency of 0.67 Hz. / As doenças cardiovasculares representam a principal causa de morte em nível mundial, sendo responsáveis por 17,3 milhões de mortes por ano. O eletrocardiograma (ECG) é uma técnica não invasiva utilizada amplamente para a detecção de algumas doenças cardiovasculares. Para aumentar a sensibilidade diagnóstica, o ECG é adquirido em ambulatório ou durante provas de esforço físico. Nessas condições de aquisição é afetado fortemente por vários tipos de ruídos, principalmente pelas flutuações de linha base (FLB). Apesar de existirem vários métodos para a eliminação das FLB, não foi identificado nenhum estudo comparativo que avalie quantitativamente estes métodos usando os mesmos sinais. Neste trabalho foi feita uma caraterização espectral das FLB onde foi comprovado que estas contem componentes espectrais em até 3,14 Hz. Tal valor, entretanto, ultrapassa os valores estabelecidos pela American Heart Association. Adicionalmente, foram implementados nove métodos para a eliminação de FLB os quais são: interpolação usando splines cúbicos, filtragem FIR, filtragem IIR, filtragem adaptativa LMS, filtragem de média móvel, análise de componentes independentes, interpolação e subtração de mediana sucessivas, decomposição em modos empíricos e filtragem wavelet. As técnicas implementadas foram avaliadas de forma qualitativa e quantitativa. Para a avaliação quantitativa foram usadas as seguintes métricas de similaridade: distância máxima absoluta, somatória do quadrado das distâncias e porcentagem da distância do erro médio quadrático. Foram realizados vários experimentos utilizando sinais de ECG sintéticos, ECG reais da QT Database, ruídos artificiais e ruídos reais da Noise Strees Test Database. Os melhores resultados foram obtidos com filtragem FIR passa-altas, com frequência de corte de 0,67 Hz.

Mobile devices users are storing more and more private and often highly sensitive information on their mobiles. Protective measures to ensure that users of mobile devices are appropriately safeguarded are thus imperative to protect users. Traditional mobile login methods, like numerical or graphical passwords, are vulnerable to passive attacks. It is common for criminal s to gain access to victims' personal information by watching victims enter their passwords into their cellphone screens from a short distance away. With this in mind, a Biometric authentication algorithm based on electrocardiogram or ECG is proposed. In this system the user will only need to touch the ECG electrodes of the mobile device to gain access. With this authentication mode no one will be able to see the biometric pattern that is used to unlock the de vices. This will increase the protection for the users. The algorithm was tested with ten subjects from MCRlab at the University of Ottawa at different days and conditions using a two electrode ECG phone case. Several tests were performed in order to reach the best setting for the algorithm to work properly. The final results show that the system has a 1.41% of chance to accept false users and 81.82% of accepting the right users. The algorithm was also tested with 73 subjects from Physionet database and the results were around the same, which confirms the consistency of the algorithm. This is the first approach on mobile authentication using ECG biometric signals and shows a promising future for this technology to be used in mobiles.

Electrocardiogram (ECG) is a noninvasive technology widely used in health care systems for diagnosis of heart diseases, and a wearable ECG sensor with long-term monitoring is necessary for real-time heart disease detection. However, the conventional ECG is restricted considering the physical size and power consumption of the system. In this thesis, we propose a Wireless ECG System with Bluetooth Low Energy (BLE) and Compressed Sensing (CS). The proposed Wireless ECG System includes an ECG sensor board based on a BLE chip, an Android application and a web service with a database. The ECG signal is first collected by the ECG Sensor Board and then transmitted to the Android application through BLE protocol. At last, the ECG signal is uploaded to the cloud database from the Android app. We also introduce Compressed Sensing into our system with a novel sparse sensing matrix, data compression and a modified Compressive Sampling Matching Pursuit (CoSaMP) reconstruction algorithm. Experiment results show that the amount of data transmitted is reduced by about 57% compared to not using Compressed Sensing, and reconstruction time is 64% less than using Orthogonal Matching Pursuit (OMP) or Iterative Re-weighted Least Squares (IRLS) algorithm. / Graduate

ECG warning system is established for real time monitoring of a patient's electrocardiogram (ECG) and automatic detection of certainement cardiac diseases, namely myocardial infarction, hyperkalemia and atrioventricular block. A distinctive research work related on the assimilation of modern technologies: software, computer and information technologies. ECG early warning system's algorithm is developed in accordance to measuring the average of the ECG signatures and Interprets the data with simulated healthy curve. The prototype system INITIALLY classifies the data and Evaluated it with natural healthy simulated curve. Meanwhile the system discards f healthy curve exists otherwise the system stores the distinguished abnormalities in the curve then transfers Warning to the doctor and patient. Cardiac patients can be assisted by this warning system by detecting abnormalities at the very early stage. Consequently, doctors Provide better tools to identify cardiac diseases resulting things more accurate medical advice

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