Biomedical Signals for Healthcare Using Hadoop Infrastructure with Artificial Intelligence and Fuzzy Logic Interpretation

Abstract

In all developing countries, the application of biomedical signals has been growing, and there is a potential interest to apply it to healthcare management systems. However, with the existing infrastructure, the system will not provide high-end support for the transfer of signals by using a communication medium, as biomedical signals need to be classified at appropriate stages. Therefore, this article addresses the issues of physical infrastructure, using Hadoop-based systems where a four-layer model is created. The four-layer model is integrated with Fuzzy Interface System Algorithm (FISA) with low robustness, and data transfers in these layers are carried out with reference health data that are collected at various treatment centers. The performance of this new flanged system model aims to minimize the loss functionalities that are present in biomedical signals, and an activation function is introduced at the middle stages. The effectiveness of the proposed model is simulated by using MATLAB, using a biomedical signal processing toolbox, where the performance of FISA proves to be better in terms of signal strength, distance, and cost. As a comparative outcome, the proposed method overlooks the conventional methods for an average percentage of 78% in real-time conditions.