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Social anxiety is a disorder where people fear social interactions and is associated with physiological changes. Eye tracking studies have shown that people with social anxiety spent more time gazing at emotional faces presented on a computer screen and spent more time gazing at the eye region. There has been limited studies on tracking eye gaze in a real-life setting interacting with another person. We used a wearable eye tracker during a brief one-on-one interview about participants’ challenges faced at work or school. Along with self-report psychological measures about social anxiety and shyness, we also measured participants’ salivary cortisol as a metric for physiological stress. We hypothesized that socially anxious individuals would have higher cortisol levels and spent more time gazing at the face. However, there was no change in cortisol levels before and after the interview. In addition, socially anxious individuals had lower cortisol levels than less anxious people. Furthermore, the time spent fixating on the region of interest (ROI), which was the face, was not correlated with social anxiety, anxiety or shyness. Paradoxically, the more socially anxious participants seem to have had a lower physiological stress response than less socially anxious participants.

Disertacijoje nagrinėjamas kompiuterinės sistemos kūrimas, su kuria būtų galima nustatyti asmens psichoemicinę būseną pagal jo balso signalų požymius. Taip pat pateikiama vyzdžio skersmens matavimo sistema. Taigi, pagrindiniai mokslinio tyrimo objektai yra žmogaus balso požymiai ir jo vyzdžio dydžio pa-sikeitimo dinamika. Pagrindinis disertacijos tikslas – sukurti metodikas ir algo-ritmus, skirtus automatiškai apdoroti ir išanalizuoti balso signalo požymius. Šių sukurtų algoritmų taikymo sritis – streso valdymo sistemos programinė įranga. Šiame darbe sprendžiami keli pagrindiniai uždaviniai: analizuojant kalbėtojo balsą, kalbančiojo psichoemocinės būklės identifikavimo galimybės ir vyzdžio dydžio kaitos dinamika. Disertaciją sudaro įvadas, keturi skyriai, rezultatų apibendrinimas, naudotos literatūros sąrašas ir autoriaus publikacijų disertacijos tema sąrašas. Įvade aptariama tiriamoji problema, darbo aktualumas, aprašomas tyrimų objektas, formuluojamas darbo tikslas bei uždaviniai, aprašoma tyrimų metodi-ka, darbo mokslinis naujumas, darbo rezultatų praktinė reikšmė, ginamieji teigi-niai. Įvado pabaigoje pristatomos disertacijos tema autoriaus paskelbtos publika-cijos bei pranešimai konferencijose ir disertacijos struktūra. Pirmajame skyriuje pateikta asmens biometrinių bei fiziologiniu požymiu analizės pagrindu sukurta „Rekomendacine biometrinė streso valdymo sistema” (angl. Recommended Biometric Stress Management System). Sistema gali padėti nustatyti neigiamą streso lygį... [toliau žr. visą tekstą] / The dissertation investigates the issues of creating a computer system that uses voice signal features to determine person’s emotional state. In addition pre-sented system of measuring pupil diameter.The main objects of research include emotion recognition from speech and dynamics of eye pupil size change.The main purpose of this dissertation is employing suitable methodologies and algo-rithms to automatically process and analyse human voice parameters. Created algorithms can be used in Stress Management System software. The dissertation also focuses on researching the possibilities of identification of speaker’s psy-choemotional state: applying the analysis of speaker’s voice parameters and the analysis of dynamics of eye pupil size change. The dissertation consists of four parts including Introduction, 4 chapters, Conclusions and References. The introduction reveals the investigated problem, importance of the thesis and the object of research and describes the purpose and tasks of the paper, re-search methodology, scientific novelty, the practical significance of results ex-amined in the paper and defended statements. The introduction ends in present-ing the author’s publications on the subject of the defended dissertation, offering the material of made presentations in conferences and defining the structure of the dissertation. Chapter 1- the Recommended Biometric Stress Management System found-ed on the speech analysis. The System can assist in determining the level of... [to full text]

Biometric identification systems have several distinct advantages over other authentication technologies, such as passwords, in reliably recognising individuals. Iris based recognition is one such biometric recognition system. Unlike other biometrics such as fingerprints or face images, the distinct aspect of the iris comes from its randomly distributed features. The patterns of these randomly distributed features on the iris have been proved to be fixed in a person's lifetime, and are stable over time for healthy eyes except for the distortions caused by the constriction and dilation of the pupil. The distortion of the iris pattern caused by pupillary activity, which is mainly due changes in ambient lighting conditions, can be significant. One important question that arises from this is: How closely do two different iris images of the same person, taken at different times using different cameras, in different environments, and under different lighting conditions, agree with each other? It is also problematic for iris recognition systems to correctly identify a person when his/her pupil size is very different from the person's iris images, used at the time of constructing the system's data-base. To date, researchers in the field of iris recognition have made attempts to address this problem, with varying degrees of success. However, there is still a need to conduct in-depth investigations into this matter in order to arrive at more reliable solutions. It is therefore necessary to study the behaviour of iris surface deformation caused by the change of lighting conditions. In this thesis, a study of the physiological behaviour of pupil size variation under different normal indoor lighting conditions (100 lux ~ 1,200 lux) and brightness levels is presented. The thesis also presents the results of applying Elastic Graph Matching (EGM) tracking techniques to study the mechanisms of iris surface deformation. A study of the pupil size variation under different normal indoor lighting conditions was conducted. The study showed that the behaviour of the pupil size can be significantly different from one person to another under the same lighting conditions. There was no evidence from this study to show that the exact pupil sizes of an individual can be determined at a given illumination level. However, the range of pupil sizes can be estimated for a range of specific lighting conditions. The range of average pupil sizes under normal indoor lighting found was between 3 mm and 4 mm. One of the advantages of using EGM for iris surface deformation tracking is that it incorporates the benefit of the use of Gabor wavelets to encode the iris features for tracking. The tracking results showed that the radial stretch of the iris surface is nonlinear. However, the amount of extension of iris surface at any point on the iris during the stretch is approximately linear. The analyses of the tracking results also showed that the behaviour of iris surface deformation is different from one person to another. This implies that a generalised iris surface deformation model cannot be established for personal identification. However, a deformation model can be established for every individual based on their analysis result, which can be useful for personal verification using the iris. Therefore, analysis of the tracking results of each individual was used to model iris surface deformations for that individual. The model was able to estimate the movement of a point on the iris surface at a particular pupil size. This makes it possible to estimate and construct the 2D deformed iris image of a desired pupil size from a given iris image of another different pupil size. The estimated deformed iris images were compared with their actual images for similarity, using an intensitybased (zero mean normalised cross-correlation). The result shows that 86% of the comparisons have over 65% similarity between the estimated and actual iris image. Preliminary tests of the estimated deformed iris images using an open-source iris recognition algorithm have showed an improved personal verification performance. The studies presented in this thesis were conducted using a very small sample of iris images and therefore should not be generalised, before further investigations are conducted.