Multi-Agent-Based Human Computer Interaction of E-Health Care System for People with Movement Disabilities

In creating of adaptive user-friendly e-health care service for people with movement disabilities, human’s affect sensing is included in Human Computer Interaction (HCI), Human-Robot Interaction (HRI), and Computer Mediated Communication (CMC) [1, 2, and 3]. In recently [4, and 5] proposed system, the model of two adaptive moving wheelchair-type robots for remotely communicating with two wearable human’s affect sensing bio-robots was used. To further development of this model, research results present the development of multi-agentbased human computer interaction model and its integration into the system of fuzzy neural control of speed of N wheelchair type robots to providing movement support for disabled individuals. An approach of filtering of skin conductance (SC) and electrocardiogram (ECG) signals using Nadaraya-Watson kernel regression smoothing in R tool for emotion recognition of disabled individuals is described and implemented in the system. The unsupervised clustering by self organizing maps (SOM) of data sample of physiological parameters extracted from SC and ECG signals noninvasively measured from disabled was proposed. It was implemented to reduce teacher noise as well as to increase of speed and accuracy of learning process of multi-layer preceptron (MLP), which was applied in the multi-agent-based human computer interaction model for online prediction of ehealth care state of disabled individuals.