Harnessing Biomedical Signals: Hadoop Infrastructure, AI, and Fuzzy Logic in Healthcare

The use of biological signals has increased dramatically in a number of developing countries, which has led to a growing interest in its integration into healthcare management systems. On the other hand, providing strong assistance for signal transmission across a communication medium is limited by the present infrastructure. Biomedical signals are complex and must be categorized at different phases in order to be sent effectively. In order to overcome these obstacles, this paper presents a new strategy that makes use of Hadoop-based systems with a four-layer paradigm. This model uses reference health data from various treatment facilities to simplify data transmission between layers when combined with the Flexible Interface Software Algorithm (FISA), which is known for having poor resilience. With this new approach, we want to improve performance by reducing the functionality losses that come with biological signals. In order to further improve signal strength, geographical separation, and cost, an activation function is included at intermediate stages. The effectiveness of the suggested approach is assessed by simulated using MATLAB and a toolkit for biomedical signal processing.