Seminar: An Intelligent WBAN system for Heart Disease Prediction Using Non-Dominated Sorting Genetic

Babak Emami
M.Sc. Thesis Proposal
Supervisor: Dr. Saeed Samet

An Intelligent WBAN system for Heart Disease Prediction Using Non-Dominated Sorting Genetic Algorithm (ITS-WBAN)

Department of Computer Science
Friday, January 29, 2016, 2:00 p.m., Room EN 2022


Abstract

Wireless Body Area Network (WBAN) is a new technique in the global telehealthcare system. Nowadays, physicians, doctors, and re-searchers are taking advantage of WBAN for having a lowcost wearable device in order to have an interactive monitoring system for remote patients. Recent studies address this issue using real time comprehensive monitoring systems based on data mining and data classi cation techniques. Applying these techniques in WBAN brings a great opportunity for physicians to have a real-time data processing and restless monitoring system. Since these algorithms such as decision tree and SVM are time-consuming methods, WBAN has not been used as an e cient prediction system. In this work, a new approach based on Non-Dominated Sorting Genetic Algorithm (NSGA) has been presented for having a real-time heart disease prediction. The proposed method (ITS-WBAN) will be capable of supporting a broad array of high-impact applications in the domain of the healthcare system, such as training, rehabilitation, surgical recovery room, and home-based monitoring healthcare system.

 

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