In the modern clinical and healthcare setting, the electronic collection and analysis of patient related vital signs and parameters are a fundamental part of the relevant treatment plan and positive patient response. Modern analytical techniques combined with readily available computer software today allow for the near real time analysis of digitally acquired measurements. In the clinical context, this can directly relate to patient survival rates and treatment success. The processing of clinical parameters, especially the Electrocardiogram (ECG) in the critical care setting has changed little in recent years and the analytical processes have mostly been managed by highly trained and experienced cardiac specialists. Warning, detection and measurement techniques are focused on the post processing of events relying heavily on averaging and analogue filtering to accurately capture waveform morphologies and deviations. This Ph. D. research investigates an alternative and the possibility to analyse, in the digital domain, bio signals with a focus on the ECG to determine if the feasibility of bit by bit or near real time analysis is indeed possible but more so if the data captured has any significance in the analysis and presentation of the wave patterns in a patient monitoring environment. The research and experiments have shown the potential for the development of logical models that address both the detection and short term predication of possible follow-on events with a focus on Myocardial Ischemic (MI) and Infraction based deviations. The research has shown that real time waveform processing compared to traditional graph based analysis, is both accurate and has the potential to be of benefit to the clinician by detecting deviations and morphologies in a real time domain. This is a significant step forward and has the potential to embed years of clinical experience into the measurement processes of clinical devices, in real terms. Also, providing expert analytical and identification input electronically at the patient bedside. The global human population is testing the healthcare systems and care capabilities with the shortage of clinical and healthcare providers in ever decreasing coverage of treatment that can be provided. The research is a moderate step in further realizing this and aiding the caregiver by providing true and relevant information and data, which assists in the clinical decision process and ultimately improving the required standard of patient care.

<p>Sudden death from arrhythmia is a major cause of mortality in the United States. Unfortunately, no current diagnostic test can accurately predict risk for sudden arrhythmic death. Because ventricular arrhythmias often result from abnormalities of repolarization, assessment of myocardial repolarization using the electrocardiogram (ECG) can aid in prediction of arrhythmia risk. Non-linear, rate-dependent changes in myocardial repolarization can promote the development of arrhythmia, but few studies examine how these dynamic changes in repolarization affect the ECG. This dissertation describes the use of a computer model to investigate the effect of dynamic changes in myocardial repolarization on the ECG T wave.</p><p>To simulate action potential conduction from the endocardium to the epicardium of the free wall of the canine left ventricle, 1-dimensional multicellular computer fiber models were created. Each fiber model was composed of endocardial, midmyocardial, and epicardial cells. For each cell type, existing mathematical models were modified to approximate experimental data for four types of dynamic repolarization behavior: (1) dynamic restitution, the response to steady-state pacing; (2) S1-S2 restitution, the response to a premature or postmature stimulus; (3) short-term memory (STM), the response to an abrupt change in pacing rate; and (4) repolarization alternans, beat-to-beat alternation in cellular repolarization time. Repolarization times were obtained from endocardial, midmyocardial, and epicardial regions in the fiber model and compared to parameters measured from a computed transmural ECG.</p><p>Spatial differences in repolarization created two voltage gradients that influenced the ECG: an endocardial-midmyocardial (endo-mid) gradient and a midmyocardial-epicardial (mid-epi) gradient. Epicardial dynamic restitution changes altered the mid-epi gradient, influencing the rising phase of the ECG T wave, and endocardial dynamic restitution changes altered the endo-mid gradient, influencing the falling phase of the T wave. Changes in epicardial or endocardial repolarization due to S1-S2 restitution or STM caused transient changes in the rising or falling phase of the T wave, respectively.</p><p>During repolarization alternans, an alternating, asymmetric distribution of extracellular potential around the fiber influenced the measurement of T-wave alternans (TWA) in the ECG. Presence of a resistive barrier in the fiber model altered the magnitude of repolarization alternans as well as the TWA amplitude in the ECG with effects dependent on barrier location. The resistive barrier also modified the relationship between cellular repolarization alternans magnitude and TWA amplitude.</p><p>The results presented in this dissertation explain basic mechanisms by which dynamic changes in myocardial repolarization affect the ECG T wave. These mechanisms form the foundation for the development of techniques to identify arrhythmogenic, dynamic changes in the myocardium using the ECG. Future studies in higher-dimensional, more complex models will build upon these results by considering the influence of additional voltage gradients, more realistic tissue geometries, and heterogeneities in the volume conductor.</p> / Dissertation

Class of 2016 Abstract / Objectives: This study assessed the feasibility of using a hand-held single lead ECG device to collect readable electrocardiograms (ECGs) in a community setting among the general population. Next, the goal was to determine if QT intervals could be measured from the collected ECGs. Additionally, this study was designed to examine if patients who had a prolonged QT interval were taking medications that are associated with an increased risk of prolonged QT interval. Methods: This prospective pilot study involved collecting ECGs via an AliveCor hand-held device at community health fairs. ECGs were evaluated for usefulness and QT intervals were measured if possible. Results: Forty-eight subjects participated in this pilot study. Forty-five viable ECGs were recorded using the hand-held device. Of the 45 ECGs, 38 were of sufficient quality to measure the QT interval and calculate QTc interval. There were no prolonged QT intervals observed in this study. Conclusions: The hand-held device recorded sufficient information to extract QT intervals for the majority of subjects. Due to the lack of prolonged QTc intervals, there was insufficient data to determine if this device could be utilized in the detection of QT prolongation due to medication use.

This work concerns with problems of the QT sequences detection in ECG signal. The first part introduces electrophysiology of heart and his electrical manifestation. For main detection were used two algorithms, which were afterwards modified and programmed in Matlab. The work includes developed custom applications for measurement and evaluation of the length of QT interval. The final lengths of the QT interval, which we got from this two methods, were compared with reference length.

This diploma thesis focuses on determination of the QT interval in ECG. The thoretical part desribes physiology of the heart, electronic activity of the heart and possible methods of ECG measurement. The theoretical part also describes methods of signal processing, the processed signal is then used for determination of the QT interval. The practical part focuses on two chosen methods of QT interval determination and on implementation of the methods in a computer program. The results part is evaluation of measured QT intervals and a comparision of the results with reference values.

První část práce je zaměřena na měření QT intervalu. QT interval může být použit k hodnocení kardiovaskulárního zdraví pacientů a detekovat potenciální abnormality. QT interval je měřen od začátku QRS komplexu až po konec T vlny. Nicméně, měření konce T vlny je často vysoce subjektivní a jeho verifikace je obtížná. Představujeme dvě metody měření QT intervalu - vlnkovou a šablonovou metodu. Metody byly porovnány mezi sebou a testovány na QT databázi. Druhá část práce je zaměřena na modelování arytmických signálů McSharryho modelem následována klasifikací s použitím umělých neuronových sítí. Metoda používá předzpracování signálů lineární aproximací a shlukování lineárních segmentů pro stanovení počátečních parametrů McSharryho modelu. Byly použity EKG signály standardní MIT/BIH Arrhythmia Databáze. Modelování bylo testováno na celé databázi a svodu MLII (modifikovaný svod II). Všechny signály mohou být modelovány 10 Gaussovými funkcemi bez významného zkreslení. Třetí část práce představuje klasifikaci EKG do dvou tříd. Předčasné komorové kontrakce (PVC) mají vysoký význam při hodnocení a predikci život ohrožujících ventrikulárních arytmií. Představujeme algoritmus pro detekci předčasných komorových kontrakcí s použitím McSharryho modelu a neuronových sítí. Signály modelované 30 Gaussovými parametry byly předloženy na vstup umělé neuronové sítě. Použitý vícevrstvý perceptron dosáhl klasifikační úspěšnosti 93,10% pro předčasné komorové kontrakce (PVC) a 96,43% pro normální stahy.

Polymorphic ventricular tachycardia (PVT) is a life-threatening arrhythmia that is typically related to long QT syndrome, organic heart disease, electrolyte abnormalities, cardiotoxic drugs, or adrenergic stimulation. A review of the literature reveals that PVT with normal QT interval and without underlying cause is quite rare. We report a case of idiopathic spontaneous PVT with structurally normal heart and without electrolyte abnormalities, drug reactions, or evidence of catecholamine induced arrhythmia. We also review the literature on the electrocardiographic characteristics and management of idiopathic PVT.

The QT interval in an electrocardiogram (ECG) reflects complex processes affecting the repolarization of ventricular myocardium. Increased QT interval variability (QTV) is thought to be caused by ventricular repolarization lability and has been associated with cardiac mortality. Recent publications have shown that template-based methods are more robust than traditional methods for QT interval extraction on a beat-to-beat basis. However, most studies are limited to non-movement ECG recordings, we want to analyze in this study the power of QT interval extraction for mobile non-stationary ECG recordings. The records of 7 test subjects are at least 65 min long and contain about 25 minutes of sport exercise such as running, cycling, sport climbing or acrobatic training. 2DSW was used to extract QT interval and best-fit distance of matched template for signal quality evaluation for each beat. Potential relations between QTV, motion and signal quality are segmentally compared. To determine motion activity we calculated normalized signal magnitude area (SMA). QTV was increased in patients during sport exercise, possibly reflects sympathetic activity in these specific physiological conditions. However, increased QTV could also be caused by low signal quality.

Long QT syndrome (LQTS) can present with syncope and seizure-like activity in the setting of torsades de pointes (TdP) with hemodynamic instability. Electrolyte abnormalities and medications can predispose to TdP in the setting of latent LQTS. An implantable cardioverter defibrillator (ICD) is needed if patients with TdP continue to be symptomatic despite medical treatment. We report a case of a patient who presented with seizures and was found to have prolonged corrected QT interval (QTc). During her admission, she was treated with ondansetron. She went into torsades de pointes and continued to have prolonged QTc. She underwent implantable cardioverter defibrillator (ICD) placement and remains asymptomatic to date.

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