A Cyber-Physical Systems Approach for Health Care Prediction

In this paper, a cyber-physical system model is proposed for usage in the medical field. The past years showed us that the challenges that the health care system is facing are becoming more and more complex. Therefore, our model aims to ease the extraction of data for each patient. For example, data like blood pressure or body temperature can be recorded and measured. The efficiency is improved by adding sensors to collect data and send it through the proposed model. The model integrates an encryption module and a machine learning module because the goal is to gather data, encrypt it to ensure privacy and train the algorithm to provide the following result: for each patient, based on their symptomatology, the algorithm will automatically analyze each variable, provide a treatment plan and predict if the health condition of a patient is getting worse. For the latter, alerts will be sent to the medical staff.