Keywords
seismocardiography; electrocardiography; MATLAB; PEP; LVET; signal processing
Abstract
There is currently a need for complementary methods for non-invasive cardiac monitoring. Seismocardiography (SCG), the measurement of cardiac-induced vibrations at the chest surface, has shown potential clinical utility. Improving the reliability of detecting fiducial points of electrocardiography (ECG) and SCG, which collectively capture the electro-mechanical cardiac activities, could expand ECG/SCG utility as a low-cost, accessible tool for clinical assessment. This study identifies commonly accepted criteria for fiducial point detection in SCG and ECG through an extensive literature review and signal processing techniques. The previous criteria were evaluated to identify their strengths and weaknesses. Based on the findings, an improved set of criteria was established for the identification of fiducial points. This study employs two complementary methods: manual and automated, to evaluate the consistency of the chosen time intervals. Manual annotations of simultaneous SCG/ECG recordings were made and compared to the automated approach results to evaluate accuracy and reliability of these results. Using a newly proposed set of fiducial point criteria, two time intervals were estimated, namely, the pre-ejection period (PEP) and left ventricular ejection time (LVET). An inverse relationship was found between LVET and heart rate, which aligned with known cardiac mechanics. In contrast, PEP remained independent of heart rate, underscoring its reliability as a reference marker for electro-mechanical event timing. These findings were further validated through comparison with existing literature, supporting the potential of SCG as a reliable, noninvasive tool for assessing cardiac function.
Thesis Completion Year
2025
Thesis Completion Semester
Fall
Thesis Chair
Mansy, Hansen
College
College of Engineering and Computer Science
Department
Mechanical and Aerospace Engineering
Thesis Discipline
Bioengineering
Language
English
Access Status
Open Access
Length of Campus Access
None
Campus Location
Orlando (Main) Campus
STARS Citation
Truong, Jasmine-Vy T., "Identification of Fiducial Points in Seismocardiographic Cycles Using Manual and Automated Annotation Methods" (2025). Honors Undergraduate Theses. 467.
https://stars.library.ucf.edu/hut2024/467
Included in
Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Biomedical Commons, Biomedical Engineering and Bioengineering Commons, Cardiology Commons, Mechanical Engineering Commons, Medical Sciences Commons, Signal Processing Commons
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