Intelektualios daugiaagentės e.sveikatos paslaugų sistemos judėjimo negalią turintiems asmenims modeliavimas

An approach is proposed in creating of an intelligent e-health care environment by modelling of an adaptive multi-agent-based ehealth and e-social care system for people with movement disabilities. Human’s Arousal Recognition Module (HARM) described based on online recognition of human’s ECG, EDA and body temperature signals by using embedded Atmega32 type microcontrollers. Multiagent based online motion control of multiple wheelchair-type robots is realized based on integration of an adaptive Fuzzy Neural Network Control algorithm into ATmega32 microcontroller. Human Computer Interaction in the system is realized in providing of necessary e-health care support actions for users with some movement disabilities by using Java–based JACK agent oriented environment. The dynamic multi-agent system is proposed to permanently realizing e-social care support actions for disabled by gathering data such as current position of robot and user‘s state information; finding decisions for given situation; sending signals to performing appropriate actions of the objects in the system

Intelektualios daugelio agentų e.sveikatos paslaugų sistemos judėjimo negalią turintiems asmenims sąsajos modeliavimas

This paper presents further development of intelligent e-health care system for people with movement disabilities. The research results present the development of multi-agent-based human computer interaction model and its integration into the system of fuzzy neural control of speed of two 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 e-health care state of disabled individuals

Modelling of ambient comfort affect reward based adaptive laboratory climate controller

There are enlarged capabilities of the Ambient Comfort Affect Reward Based Laboratory Climate Controller (ACAR-Controller) by developing and integrating of the Heating/Ventilation/Air Conditioning (HVAC) and the Red- Green-Blue-Yellow (RGBY) Light Emitting Diode (LED) lighting sub-models of one room laboratory in the ACARController model. The model was validated by implementation and testing of the following elements of the laboratory prototype of ACAR-Controller: a) the sustainable electric power distribution subsystem; b) the intelligent RGBY LED lighting subsystem; c) the non-invasive measuring subsystem of human reaction to comfort conditions in the laboratory; d) the ATMEGA128RFA1-ZU transceivers based wireless communication subsystem; e) the software for the ACARController

Intelektualios daugelio agentų e.sveikatos paslaugų sistemos judėjimo negalią turintiems asmenims sąsajos modeliavimas

This paper presents further development of intelligent e-health care system for people with movement disabilities. The research results present the development of multi-agent-based human computer interaction model and its integration into the system of fuzzy neural control of speed of two 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 e-health care state of disabled individuals