USER’S STATE NORMALIZATION COMPUTERIZED SYSTEM WITHIN AN INTELLIGENT FEEDBACK

 

SECTION 4. Innovation technologies.

Shabatura Maksym 

National University «Lvivska Polytechnika», Lviv, Ukraine

 

USER’S STATE NORMALIZATION COMPUTERIZED SYSTEM WITHIN AN INTELLIGENT FEEDBACK

 

This paper provides a brief preview for certain scientific basics of functional and algorithmic aspects of an unique computerized system, capable for performing user’s state  normalization procedure in case of deviation from desired optimal state.

The creation of described system within an intelligent feedback that could effectively normalize the user’s state isn’t relevant only in scientific terms, but also has a great common practical value for expanding the scope of “negotiation” betwean users and computer systems [1, 2]. The functional structure of designed system mentioned on figure 1. System includes both special software and hardware.

 

 

Fig.1. Functional structure of user’s state normalization computerized system within an intelligent feedback

The principle of an intelligent feedback based on the automatic adaptive functioning, chained on “special interaction” betwean user and computerized system with servicing by special system of sensors, that includes: breathing, temperature, pressure and tachycardia detectors. User’s state impact system based on special audio and visual irritants usage.

One of the most significant module is an application module D – identification of current user’s state, presented by unique algorithm that consists within 2 stages (figure 2). Mathematical apparatus based on fuzzy-logic adaptive analysis [3, 4].

 

Fig.2. The first stage of an identification algorithm

 

The second stage of proposed algorithm is needed to bring more accuracy for decision making about current user’s state identification (figure 3).

 

 

Fig.3. The second stage of an identification algorithm

Conclusion

This paper dedicated for acquaintance with investigation and elaboration of user’s state normalization computerized system within an intelligent feedback.

Presented the functional structure and an identification algorithm of described system.

Literature

  1. Haupt Randy, Haupt Sue Ellen, “Practical Genetic Algorithms”, Second Edition, Wiley-Interscience, 2004. 
  2. Russell Stuart, Norvig Peter, “Artificial Intelligence: A Modern Approach”, Third Edition, Prentice Hall, 2009. 
  3. Shabatura Maksym “Computerized system for user’s state identification with intelligent feedback”/Ukrainian, p.281-291, “Information systems and nets”, The Bulletin of Lviv Polytechnic University, №699, 2011. 
  4. Zadeh, L. A. et al. Fuzzy Sets, Fuzzy Logic, Fuzzy Systems, World Scientific Press, 1996.