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Using our tools backwards, AF detection by confusing time and frequency

Kraaijeveld, Michael (author)

Atrial Fibrillation or AF is the most common heart rhythm anomaly affecting millions of people. This work explores the possibilities of reinterpreting speech processing techniques for use in atrial fibrillation detection. An existing method of modelling single heartbeat, single lead ECG signals by means of an ARMA model's amplitude response as a...

master thesis 2024

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Interpretable Parametric Modelling of the Heart based on ECG Signals

Wang, Chengyan (author)

Atrial fibrillation (AF) is one of the most common heart diseases. Billions of people have suffered from it in the world. Although it can lead to terrible complications such as stroke and heart failure, the underlying mechanisms of it are still under-explored. Besides, there is no so-called optimal therapy for the patients. As the disease is...

master thesis 2023

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Design and prototyping of an ECG simulator for medical device testing in low-resource settings

Graell Collado, Anna (author)

Ensuring reliable and safe performance of medical devices in healthcare institutions is crucial for the wellbeing of patients. For this, physiological simulators may be used, which provide reference signals to compare against. The usage of physiological simulators, such as ECG simulators, as medical device testers is widely extended in high...

master thesis 2023

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Energy-efficient Spike Encoding for ECG Arrhythmia Classification

Dong, Yingzhou (author)

Cardiovascular diseases (CVDs) are the top cause of death worldwide, and their diagnosis can be quickly and painlessly achieved through Electrocardiogram (ECG). The diagnosis of electrocardiogram has gradually evolved from manual diagnosis by doctors to one that can be realized using Artificial Intelligence (AI). Early AI still required manual...

master thesis 2023

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Short Duration ECG into Autoencoder Followed By Clustering: An Explorational Study

van den Bos, Sjoerd (author)

Electrocardiography is the craft of producing electrocardiograms. These graphs give physicians insight into the potential pathology of the heart. In order to come to a diagnosis, physicians use electrocardiograms in combination with follow-up physical examinations. There has been extensive research into automated methods that can differentiate...

master thesis 2022

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Communication protocols: For a wireless ECG solution

Custers, Geert (author), Loen, Stefan (author)

This report is part of the WiECG project. The goal of the WiECG project is to create a prototype device that makes it possible to perform a 12-lead ECG on patients without wires from a patient to the monitor. The solution consists of a transmitter and receiver of which one is close or on the patients body and the other is connected to a monitor....

bachelor thesis 2022

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Accurate and Energy-efficient ECG Classification using RRAM based DNN Architecture

Dash, Sudeshna (author)

Cardiac arrhythmia characterized by irregular heartbeats is a prevalent problem among people suffering from cardiovascular diseases (CVD). Abnormalities in the heartbeats manifested in the electrocardiogram (ECG) signal are traditionally analysed by expert cardiologists or semi-automated computer aided techniques, which can be time consuming....

master thesis 2021

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ECG Artefact Suppression and External Data Synchronization with the Medtronic Percept, a Deep Brain Stimulator with Sensing Technology

Stam, Mariëlle (author)

Deep brain stimulation (DBS) is used to treat a variety of movement disorders. In current DBS therapy, the stimulation parameters are manually adjusted based on a subjective assessment of patient’s symptoms. State-of-the-art DBS research focuses on recording brain activity to create a patient-specific neuronal profile that correlates with the...

master thesis 2021

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An ECG- and PPG-Based Wearable Atrial Fibrillation Detection Device: Signal Acquisition

Kohabir, Amar (author), Smit, Alex (author)

When symptoms of atrial fibrillation (AF), a common cardiac arrhythmia, are experienced, a Holter monitor or event recorder is used for official diagnosis. Apart from the fact that these devices are experienced as inconvenient, AF can already manifest damage in a pre-symptomatic phase. This thesis is aimed at developing a method for recording...

bachelor thesis 2021

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Atrial Fibrillation classification from a short single lead ECG recording

Yin, Yuchen (author)

This thesis focuses on classifying AF and Normal rhythm ECG recordings. AF is a common arrhythmia occurring in millions of people every year, which could lead to blood clots, stroke or even heart failure. When AF is occurring, the P waves are often absent and RR intervals are often irregular. <br/><br/>This thesis proposes a new Poincaré plot...

master thesis 2020

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Stress Detection System Using ECG and Respiratory Signals

Meijer, I.D. (author), Morssink, B.J.C. (author)

There are many different studies that try to use physiological features to determine stress. But there exists a lot of uncertainty about which physiological signals and features are the best classifiers and a lot of discrepancies in classification accuracies exist. This study proposes a novel method for the detection of stress. This method contains...

bachelor thesis 2020

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Thesis Pre-Processing ECG & Respiratory Signals for Detection of Stress

Kuruoğlu, T. (author), Kinaci, E. (author)

The main purpose of this thesis is the removal of different kinds of artifacts from incoming signals and the identification of relevant information which can be utilized for further analysis. This thesis proposes two designs which are used for the pre-processing of the electrocardiogram (ECG) signal and the respiratory signal. The ECG signal...

bachelor thesis 2020

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Seizure preventing MBAN

Henstra, Joris (author), Jansen, Pim (author)

Many people worldwide suffer from epileptic seizures and not all of them can be prevented using medicines, this thesis is being done for seizure prevention. This is based on implementing a medical body area network (MBAN) that takes sensory recordings across the whole body. This is needed as the research group that proposes this project found...

bachelor thesis 2020

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Monitoring selectively directed auditory attention using physiological synchrony in EEG, electrodermal activity and heart rate

Stuldreher, Ivo (author)

Monitoring selectively directed auditory attention in groups can be helpful in a range of contexts, such as in education. In real-world settings, selectively directed attention cannot be monitored by relating physiological signals to known event markers. Determining the similarity of physiological responses across individuals in a group (i.e.,...

master thesis 2019

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Heart rate, heart rate variability, and GSR in relation to motion sickness caused by lateral vehicle motion

Lie Hok Lien, Kenny (author)

Self-driving cars is considered the next major step in the automotive industry and with automation in passenger vehicles, the driver can benefit from the freed up time for leisure or work, as he or she becomes the passenger. However, this is only possible if the drivers are comfortable during automated driving. The major issue here, is that the...

master thesis 2019

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An automated ECG signal quality assessment method with supervised learning algorithm

Wang, Yuyang (author)

Wearable health has become a striking area in our daily life.<br/>Electrocardiogram (ECG) is one of the biomedical signals collected by the wearable or portable devices, which is widely used in heart rate monitoring and cardiac diagnosis. However, automatic ECG signal analysis is difficult in real application because the signals are easy to be...

master thesis 2018

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Design Space Exploration of a Neuromorphic ECG Classification System using a Spiking Self-Organizing Map

Mes, Johan (author)

The Self-Organizing Map (SOM) is an unsupervised neural networktopology that incorporates competitive learning for the classicationof data. In this thesis we investigate the design space of a system incorporating such a topology based on Spiking Neural Networks (SNNs), and apply it to classifying electrocardiogram (ECG) beats. We present novel...

master thesis 2018

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Motion artefact reference sensor study for ECG signals

Bisht, Anirudh (author)

ECG signals captured almost always have motion artefact noise. This noise arises due to relative motion between the ECG electrode and skin. To remove this noise a reference signal is required that correlates to the noise. This thesis presents the design and test results of a prototype system that incorporates various motion sensors into an ECG...

master thesis 2018

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Energy Efficient Feature Extraction for Single-Lead ECG Classification Based On Spiking Neural Networks

Kolağasioğlu, Eralp (author)

Cardiovascular diseases are the leading cause of death in the devel- oped world. Preventing these deaths, require long term monitoring and manual inspection of ECG signals, which is a very time consum- ing process. Consequently, a wearable system that can automatically categorize beats is essential.<br/>Neuromorphic machines have been introduced...

master thesis 2018

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ECGraph: Design of a 12-Lead electrocardiographic system for home use

Steijlen, A. (author)

This master thesis presents the development of a 12-lead electrocardiographic system for home use. The project focusses on the product design aspects of this system. By doing thorough context and user research it is aimed to an accessible product service system for the patient as well as the healthcare professional. Two cardiologists from the...

master thesis 2017