As we all know the classical set theory has a deep-rooted influence in the traditional mathematics. According to the two-valued logic, an element can belong to a set or cannot. In the former case, the element’s membership degree will be assigned to one, whereas in the latter case it takes the zero value. With other words, a feeling of imprecision or fuzziness in the two-valued logic does not exist. With the rapid development of science and technology, more and more scientists have gradually come to realize the vital importance of the multi-valued logic. Thus, in 1965, Professor Lotfi A. Zadeh from Berkeley University put forward the concept of a fuzzy set. In less than 60 years, people became more and more familiar with fuzzy set theory. The theory of fuzzy sets has been turned to be a favor applied to many fields. The study aims to apply some classical and extensional methods of fuzzy set theory in life expectancy and treatment prognoses for cancer patients. The research is based on real-life problems encountered in clinical works by physicians. From the introductory items of the fuzzy set theory to the medical applications, a collection of detailed analysis of fuzzy set theory and its extensions are presented in the thesis. Concretely speaking, the Mamdani fuzzy control systems and the Sugeno controller have been applied to predict the survival length of gastric cancer patients. In order to keep the gastric cancer patients, already examined, away from the unnecessary suffering from surgical operation, the fuzzy c-means clustering analysis has been adopted to investigate the possibilities for operation contra to nonoperation. Furthermore, the approach of point set approximation has been adopted to estimate the operation possibilities against to nonoperation for an arbitrary gastric cancer patient. In addition, in the domain of multi-expert decision-making, the probabilistic model, the model of 2-tuple linguistic representations and the hesitant fuzzy linguistic term sets (HFLTS) have been utilized to select the most consensual treatment scheme(s) for two separate prostate cancer patients. The obtained results have supplied the physicians with reliable and helpful information. Therefore, the research work can be seen as the mathematical complements to the physicians’ queries.

Emocijų atpažinimas, tiriant žmogaus fiziologinius parametrus, yra labai aktualus šiuolaikinės informatikos mokslo uždavinys. Šio darbo siekis yra suprojektuoti emocijų atpažinimo sistemos prototipą, kurį su minimaliais kaštais galima būtų pritaikyti įvairiose emocijomis grindžiamose sistemose. Pateikiamas tokios sistemos koncepcinis modelis, susidedantis iš aparatūrinės įrangos ir programinio modelių. Fiziologinių signalų stiprinimui naudojami AD620 ir OP97 operaciniai stiprintuvai. Analoginio signalo keitimas ir perdavimas į kompiuterį atliekamas naudojant Atmega16 mikrovaldiklį. Schemų testavimui naudojamas kompiuterinis oscilografas (PCS500). Atliekamas skaitmeninio signalo filtravimo metodų tyrimas. Pristatomi fiziologinių parametrų fiksavimo metodų (EKG, SC) atpažinimo algoritmai, pagrįsti SVW algoritmu. Atliekama HRV spektrinė analizė į dažninę sritį, naudojant Furjė transformacijas. Pateikiama praplėsta neraiškioji valdymo sistema, kuri iš fiziologinių parametrų (HR, HRVL, HRVH, SCR, STpirštas, STgalva) išveda susijaudinimo–valentingumo laipsnius. Pagal šiuos laipsnius išvedamos emocijos. Aptariami sukurtų algoritmų, realizuojant juos realioje aplinkoje, nauji elgsenos charakteristikų ypatumai. / Very important task of modern computer science is emotion recognition by human physiological parameters. The purpose of this work is to design a prototype of emotion recognition system, which could be possible customize in various emotions systems with minimal costs. There is representing such system conceptual model, which consists from them realization hardware and programme models. For amplifying the physiological signals is using instrumental AD620 and high precision OP97 operations amplifiers. Analogical signal converting to digital and transmitting to the computer redundant by Atmega16 microcontroller. For electrical schemas testing is using oscillograph (PCS500) connected on the computer. It is redundant analysis for digital signal filtering methods. There is presenting the recognition algorithms, based on SVW algorithm, for physiological parameters fixing methods (ECG, SC). For HRV spectral analyze in frequency domain it is using Furies transformations. There is extended fuzzy control system, which deduces arousal–valence levels from physiological parameters (HR, HRVL, HRVH, SCR, STfinger, SThead). By theses levels is deduces emotions. The new characteristical singularities of designed algorithms in real environment are also discussed.