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System Design for Data Analysis with Multiscale Entropy

An engineered lightweight architecture has been used on the server side for different purposes. One of them was to provide an environment for data collection and analysis. Since most of the data analysis is static- and post-process, there is a challenge to apply existing data analysis to data collected in real time. In this paper, we propose an architecture that uses the multiscale entropy analysis (MSE) method to analyze data. This system was used to analyze real electrocardiogram (ECG) data in pseudo real-time. The architecture is divided into three parts: (1) a lightweight back-end system that includes Node.js, MongoDB, Nginx, (2) the use of physiological data from PhysioNet to simulate a real-time environment, and (3) the use of MSE to analyze the simulated data. The current findings are beneficial to the community of health science since it removes the necessity of setting up a real-time environment in order to run the tests on new algorithms and methods.