Modelling of Intelligent Multi-Agent based E-health Care System for People with Movement Disabilities

In creating of adaptive user-friendly e-health careservice for people with movement disabilities, human’saffect sensing may be helpful. Being able both to providean intelligent accident preventive robot-based support forpeople with movement disabilities and to include affectsensing in Human Computer Interaction (HCI), Human-Robot Interaction (HRI), and Computer MediatedCommunication (CMC), such system depends upon thepossibility of extracting emotion without interrupting theuser during HCI, HRI, or CMC [1, and 2].The features of continuous physiological activity ofdisabled person are becoming accessible by use ofintelligent bio-sensors coupled with computers. Suchsensors provide information about the wearer's physicalstate or behavior. They can gather data in a continuous waywithout having to interrupt the user and may includesensors of: Galvanic Skin Response (GSR) orElectrodermal Activity (EDA), Blood Volume Pulse(BVP), Electrocardiogram (ECG), Respiration,Electromyogram (EMG), Body temperature (BT), andFacial Image Comparison (FIC). Galvanic Skin Response,the GSR, is a measure of the skin's conductance betweentwo electrodes that apply a safe, imperceptibly tiny voltageacross the skin of subject's fingers or toes. An individual'sbaseline skin conductance will vary for many reasons,including gender, diet, skin type and situation. When asubject is startled or experiences anxiety, there will be afast increase in the skin's conductance (a period ofseconds) due to increased activity in the sweat glands(unless the glands are saturated with sweat). After a startle,the skin's conductance will decrease naturally due toreabsorption. Sweat gland activity increases the skin'scapacity to conduct the current passing through it andchanges in the skin conductance reflect changes in thelevel of arousal in the sympathetic nervous system. Anumber of wearable systems have been proposed withintegrated wireless transmission, GPS (Global PositioningSystem) sensor, and local processing. Commercial systemsare also becoming available. For example, CardioNetprovides a remote heart monitoring system where ECGsignals are transmitted to a PDA (Personal DigitalAssistant) and then routed to the central server by using thecellular network. Pentland [1] recently presented thewearable MIThril system where ECG data, GPS position,skin temperature and galvanic skin response can becaptured by a PDA. Most this type hardware platforms aredesigned for network research, environment monitoring ortracking applications, such as Berkeley’s Mica2 and Telos,ETH’s BTnodes, Intel’s iMote and UCC’s DSYS25.Although there are a number of context aware sensingplatforms such as the SmartITs and the MITes(see