Disease Diagnosis and Data Protection System for IoT-based Wearable Sensor Network

Big Data analytics is used in many areas of smart healthcare. Leakage or correction of this data while transferring is not only violating patients' privacy but endangering their exists. Many scientists have worked on encoded Personal Health Records. Conversely, around are quiet contests such as data leak while learning, training models outflow and exactly operators don't like to breach their statistics in the analytics organization. This paper presents a method for forecasting disease and alerts, and using Empirical Mode Decomposition (EMD) and Support Vector Regression (SVR) to analyze and display patient health information. In order to defend health data privacy, we approve a secure data deletion method, whereby the information owner will be able to choose to deny some users admission to their health data. The presented analysis and the experimental results show the safety and efficacy of our proposed approach.