A methodology for optimizing the selection and storage of ultra-high-resolution electrocardiogram information

Purpose of research. Development and testing of a specialized automated system for recording, structured storage, and analysis of ultra-high-resolution electrocardiogram data obtained during experiments modeling myocardial ischemia in laboratory animals using a new ultra-high-resolution electrocardiography method is the purpose of research.

Methods. To address this problem, an automated system consisting of recording, storage, and analysis modules was implemented. The recording module was specifically designed to store UHR ECS and includes the ability to visualize the experiment progress to monitor the condition of the biological sample. The experimental data storage module consists of a document-oriented database and specialized software that enables systematization and retrieval of heterogeneous information based on specified criteria. The automatic analysis module sequentially executes software modules specifically designed for analyzing UHR ECS.

Results. The introduction of a developed system for storing and analyzing a large amount of ultra-high resolution electro-cardio signal data obtained during experiments made it possible to significantly optimize research processes. The approach used made it possible to speed up the completion of routine operations by automating the data processing cycle from recording and system optimization to analysis. The absence of manual assignment of metadata, as well as subsequent validation, eliminates unstructured information storage and human errors, allowing previously unavailable meta-analysis.

Conclusion. The system ensures reliable storage and secure access to large volumes of heterogeneous data, improving the reproducibility, quality, and effectiveness of studies on the early diagnosis of myocardial ischemia using ultra-high-resolution electrocardiography.

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