Wireless Body Area Networks (WBAN) helps in pervasive health monitoring of a patient, thus assists doctors in diagnostics. WBAN nodes on the patient communicates with the doctor at any remote place and informs the patients’ condition. In this paper, the mathematical modelling techniques, which assist in decision-making, namely TOPSIS, Integer Linear Programming and Fuzzy Logic are analyzed effectively.So decision making can easily help for analyzing and finding a suitable decision. WBAN diagnoses’ in real-time. The proposed methodologies using different types of decision making systems will definitely help the patient in terms of real-time monitoring of his data through IoT. Electronic Medical Records are updated within certain time periodically via standard mobile devices such as smart-phones and Personal Digital Assistants. The results give a better understanding of healthcare analytics for WBAN for assisting patients with WBAN sensors. The simulation results and analysis of different decision making methods are discussed . There is an expert repository of multiple doctors at a remote place. The patient’s details are stored in the hospital server which can be used by remote doctors for any analysis. The patient is monitored continuously by a doctor and data is remotely acquired. In case of any emergency, the doctor advises an e-prescription to the nurse, so she takes an immediate required action. All these proposed schemes are fast and reliable decision methods for WBAN. These methods has a significant impact on WBAN. In future, this technology will be tried with different patients and analysis will be done in terms of network longevity and six V’s. © BEIESP.