Πλοήγηση ανά Συγγραφέας "Basdani, Asimina"

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    Electrocardiogram (ECG) monitoring system using low-cost IOT device
    (ΕΛΜΕΠΑ, Σχολή Μηχανικών (ΣΜΗΧ), ΠΜΣ Μηχανικών Πληροφορικής, 2024-07-04) Basdani, Asimina; Μπασδάνη, Ασημίνα; Panagiotakis, Spyridon; Παναγιωτάκης, Σπυρίδων
    The modern technological advances can be the centerpiece of a new health-care model that can improve the quality and quantity of life. Cardiovascular diseases are the leading cause of death globally. For this reason, it might be essential for those with long-term cardiac conditions to have access to health technologies which are affordable and with long availability. Internet of Things (IoT) is well-known for its ability to serve as a tool for cardiac monitoring that can support the identification of heart diseases and, hence, to save lives. In this context, an Electrocardiogram (ECG) Monitoring System utilizing a low-cost Internet of Things device could represent a cost-effective and accessible solution for continuous cardiac health monitoring. In this thesis we attempt to develop and evaluate such a system. Our system integrates ECG sensors with budget friendly IoT devices enabling real-time data acquisition and transmission to a cloud computing infrastructure for ECG signal analysis. The implementation of our node for heart monitoring is based on the AD8232 heart rate sensor and the esp32 microcontroller by Espressif. The portable sensor, using 3-lead cable-electrodes, measures patients’ heart rate activity and the microcontroller transmits on-the-fly via a WiFi connection the collected digital ECG data to the cloud. At the server side, data storage, processing and visualization for additional analysis take place in the Ubidots IoT platform. There, the ECG signals are analyzed, and critical metrics, including Heart Rate (HR), RR interval, PR interval, QRS complex, QT interval and QTc interval, are extracted and projected using a custom algorithm written in python to support a diagnosis. This thesis evaluates the accuracy of the ECG recordings captured by the proposed 3-lead ECG monitoring system against the standard 12-lead ECG clinical devices. The evaluation aims to assess the validity and reliability of the proposed 3-lead ECG monitoring system, offering valuable insights for its potential integration into clinical practice. Additionally, it includes an assessment of our custom algorithm for ECG analysis by juxtaposing measurements from our system with data from the physiobank database of known ECG signals and data from ECG generator application. This custom system using state-of-the-art technologies to deliver high-quality ECG data in realtime, can be a priceless tool for both patients and physicians, since it can help the fight for early detection and proactive management of cardiac conditions with its portability, simplicity of use, and potential for remote monitoring.