Faculty of Computer Science and Engineering

Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5

The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest faculties in that field in the region. The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.

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Language: search.filters.language.English (United States)Subject: search.filters.subject.electrocardiogram

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    Processing MIMIC-III for Evaluation of Various Blood Pressure Estimation Models
    (2024)
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    Kuzmanov, Ivan
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    Lehocki, Fedor
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    Madevska Bogdanova, Ana
    The development of non-invasive easily available blood pres- sure estimation methods using electrocardiogram - ECG and/or photo- plethysmogram - PPG signals has gained increasing attention. However, there is a lack of consistency in the evaluation of these methods due to variations in the size and availability of data in published datasets. Our research involves retrieving, cleaning, and storing a portion of the MIMIC-III database for utilization in model training and testing. This paper outlines our methodology for processing the MIMIC-III database, along with the challenges encountered during the process.
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    Integrated Smart Patch for Heart Rate and Respiratory Rate Monitoring
    (IEEE, 2023-07)
    Daniel Gogola
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    Richard Bagín
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    Madevska Bogdanova, Ana
    A wearable smart patch was designed to monitor the vital parameters of mass casualties’ victims after the first triage. The device captures ECG, PPG, and respiration signals and triggers an alarm if the heart rate (HR) or respiration rate (RR) exceeds the specified limits and indicates a threat to the victim's life. To obtain a robust and reliable solution, the same parameters are derived from two or three independent signals. In this study, ECG signals have been recorded from different positions on the chest, and the performance of several algorithms for HR and RR extraction was tested. The initial measurements show that HR estimation is more accurate and reliable than RR estimation. The best results, considering both, the HR and RR calculations, were achieved when Pan-Tompkins’s algorithm was used, and ECG electrodes were placed vertically on the right anterior chest. Increasing the length of the evaluated ECG signal above 30 seconds did not significantly affect the HR and RR calculation, regardless of the algorithm used.