Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 25 for “"ECG signal"”.
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Detection Of The R-wave In Ecg Signals
… a new approach for detecting R-waves in the ECG signal and generating the corresponding R-wave impulses with the delay between the original R-waves and the R-wave impulses being lesser than 100 ms. The algorithm was implemented in Matlab and tested with good results against 90 different ECG …
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Motion artifact reduction of electrocardiograms using multiple motion sensors
An electrocardiogram (ECG) is a measurement of the electrical signal produced by the heart as it beats. This is a signal very commonly used by medical professionals, as it gives an indication of an individual’s heart rate and can further be used to detect specific abnormalities within the heart. …
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A tale of two time series methods : representation learning for improved distance and risk metrics
… adverse outcome. We use segments of a patient's ECG signal to predict that patient's risk of cardiovascular death within 90 days. In contrast to other work, we work directly with the raw ECG signal to learn a representation with predictive power. Our method produces a risk metric for …
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Novel ECG analysis with application to atrial fibrillation detection
A new approach of electrocardiography (ECG) analysis system is developed to process noisy ECG signals leading for improved arrhythmia detection. The system employs two processing units comprising a novel noise reduction unit and a novel pattern recognition unit. Each unit incorporates numbers of …
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SPARSE RECOVERY BY NONCONVEX LIPSHITZIAN MAPPINGS
… mathematics and computer science, especially in signal and image processing fields. The general framework of sparse representation is now a mature concept with solid basis in relevant mathematical fields, such as probability, geometry of Banach spaces, harmonic analysis, theory of computability, …
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An Authentic Ecg Simulator
An ECG (electrocardiogram) simulator is an electronic tool that plays an essential role in the testing, design, and development of ECG monitors and other ECG equipment. Principally an ECG simulator provides ECG monitors with an electrical signal that emulates the human heart's electrical signal so …
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Control and monitoring of an intra-aortic balloon pump for cardiac assist
… to the spectrum within which the R-wave of an ECG signal lies. A safety circuit to prevent the heart pumping against an inflated balloon is incorporated. History of the 8 secs preceding any instant is available. A description of the medical tests carried out so far is given.
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PROCESSING AND CLASSIFICATION OF PHYSIOLOGICAL SIGNALS USING WAVELET TRANSFORM AND MACHINE LEARNING ALGORITHMS
Over the last century, physiological signals have been broadly analyzed and processed not only to assess the function of the human physiology, but also to better diagnose illnesses or injuries and provide treatment options for patients. In particular, Electrocardiogram (ECG), blood pressure (BP) …
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Towards short-term forecasting of ventricular tachyarrhythmias
… reports the discovery of spectral patterns in ECG signals that exhibit a temporal behavior correlated with an approaching Ventricular Tachyarrhythmic (VTA) event. A computer experiment is performed where a supervised learning algorithm models the ECG signals with the targeted behavior, applies …
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Heartbeat location assistance for electrocardiograms
"The electrocardiogram (ECG) is the main source of heartbeat analysis throughout the medical community, due to the distinctive appearance of the QRS complex at the time of each beat. There are other signals that also exhibit distinctive patterns at the time of each heartbeat; however, the ECG is …
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Machine learning classifiers for critical cardiac conditions
… require a manual and visual analysis of ECG and heart rate (RR interval) data. In this thesis, novel features and machine learning classifiers are developed for automating the detection of Congestive Heart Failure (CHF) and Atrial Fibrillation (AFIB). These classifiers can potentially …
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Correlation analysis between the EEG parameters and the parameters derived from ECG and Steering wheel related signals for driver drowsiness detection
Physiological signals such as Electroencephalography (EEG), Electrocardiography (ECG) and nonphysiological signals such as steering wheel related parameters have been investigated for drowsiness detection in previous researches. EEG has been deemed as a reliable way to detect drowsiness; while the …
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Optimizing Real-Time ECG Data Transmission in Constrained Environments
ECG monitoring systems have a significant role in detecting cardiovascular diseases and reducing the rate of sudden cardiac deaths through early warnings for heart attacks. One of the critical factors in supporting real-time ECG tracking is to guarantee monitoring system availability. This thesis …
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A Physiological Signal Processing System for Optimal Engagement and Attention Detection.
… system which uses fundamental physiological signals such as the Electrocardiograph (ECG), to analyze and predict the presence or lack of cognitive attention in individuals during task execution. The primary focus of this study is to identify the correlation between fluctuating level of …
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Power efficient machine learning-based hardware architectures for biomedical applications
… of two physiological sensor data, such as ECG signal from the chest movement and SpO2 measurement from the pulse oximeter to predict the occurrence of SA episodes. In the training phase, actual patient data is used, and the network model is converted into the proposed hardware models to …
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Assessing the Re-Identification Risk in ECG Datasets and an Application of Privacy Preserving Techniques in ECG Analysis
<p>In this work, first we investigate the use of ECG signal as a biometric in human identification systems using deep learning models. We train convolutional neural network models on ECG samples from approximately 81k patients. Our models achieved an over-all accuracy of 95.69%. Further, we assess …
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LOW POWER AND HIGH SIGNAL TO NOISE RATIO BIO-MEDICAL AFE DESIGN TECHNIQUES
… to enable high-quality Electrocardiography (ECG) sensing. Usually, an ECG signal and several bio-medical signals are sensed from the human body through a pair of electrodes. The electrical characteristics of the very small amplitude (1u-10mV) signals are corrupted by random noise and have a …
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Sparse Representation and its Application to Multivariate Time Series Classification
In signal processing field, there are various measures that can be employed to analyse and represent the signal in order to obtain meaningful outcome. Sparse representation (SR) has continued to receive great attention as one of the well-known tools in statistical theory which among others, is used …
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Sparse Representation and its Application to Multivariate Time Series Classification
In signal processing field, there are various measures that can be employed to analyse and represent the signal in order to obtain meaningful outcome. Sparse representation (SR) has continued to receive great attention as one of the well-known tools in statistical theory which among others, is used …
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Automatické rozpoznání kvality signálů EKG
Tato diplomová práce řeší problematiku automatického odhadu kvality EKG signálů. Hlavním cílem práce je na základě nastudovaných metod realizovat vlastní algoritmus pro rozdělení signálu EKG do tří tříd kvality. Teoretická část práce obsahuje především popis snímání elektrické aktivity srdce, …
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