Telemonitoring System Architecture for Emotion Recognition with WBSN and Ensemble Learning

Abstract

Telemonitoring provides a set of technologies that enables remote monitoring of patients with critical health conditions.Wireless Body Area Networks (WBAN) technology has emerged as a major factor contributor to the need for ubiquitous healthcare.It provides a real-time telemonitoring system to treat several chronic diseases using wireless biosensors.The first standard to support communication between biosensors is IEEE 802.15 Task Groups 6 (TG6). The standard regulates the communication in,on or inside the human body for a short-range and low power wireless communications.IEEE 802.15.6 operates on a Medium Access Control (MAC) layer that supports several Physical (PHY) layers such as narrowband (NB),ultra-wideband (UWB),and human body communication (HBC).In this paper,a realtime telemonitoring system architecture for EEG brainwave emotion recognition is presented.The system aims to collect EEG data and forward them to clinicians in order to detect the evolution of the monitored diseases based on brain wave emotion analysis.Ensemble Learning techniques are used for decision making to discern the current health state of the patient.