No description available.

Cognitive theories of depression have long posited automatic interpretation biases (AIB) as a central contributor to depressed mood. The current study was first to examine AIB in a clinically defined depressed sample. While assessing AIB using a semantic association paradigm, pupillary reactivity was simultaneously recorded to build insight into the AIB process. A total of 53 individuals (25 depressed and 28 healthy control) completed the Word Sentence Association Paradigm for Depression (WSAP-D) while pupillary reactivity was recorded. Results revealed the depressed group was significantly more likely to endorse negative AIB and less likely to endorse benign AIB compared to healthy controls. The depressed group demonstrated a modest effect size difference indicating they were faster to endorse negative AIB compared to the healthy controls, but did not differ in endorsing benign AIB or in rejecting either valence. Pupillary reactivity was found to differentiate behaviorally defined AIB type from a natural processing condition when counter to theorized, group relevant AIB. The depressed group demonstrated greater initial pupillary constriction during initial presentation of ambiguous information and comparatively less pupillary dilation during and after endorsing a benign AIB. Taken together, the results suggest that theorized negative AIB and lack of benign AIB are characteristic of depression, that greater cognitive effort is required to reject interpretations consistent with theorized biases consistent with reinterpretation processes, and that depressed individuals are less engaged with benign AIB compared to healthy controls, possibly associated with hedonic deficits. Theoretical implications and future directions are discussed.

No description available.

Recent research has indicated that the pupil diameter (PD) in humans varies with their affective states. However, this signal has not been fully investigated for affective sensing purposes in human-computer interaction systems. This may be due to the dominant separate effect of the pupillary light reflex (PLR), which shrinks the pupil when light intensity increases. In this dissertation, an adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a processed MPD (PMPD) signal, from which a classification feature, PMPDmean, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of stress states in the subject from whom the pupil diameter signal was recorded, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of stress and relaxation states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. The discriminating potential of each individual feature extracted from GSR, BVP and PD was studied by analysis of its receiver operating characteristic (ROC) curve. The ROC curve found for the PMPDmean feature encompassed the largest area (0.8546) of all the single-feature ROCs investigated. The encouraging results seen in affective sensing based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the benefits of using the AIC implementation with the HITV adaptive algorithm to isolate the PAR and the potential of using PD monitoring to sense the evolving affective states of a computer user.

As the amount of information captured about users increased over the last decade, interest in personalized user interfaces has surged in the HCI and IS communities. Personalization is an effective means for accommodating for differences between individuals. The fundamental idea behind personalization rests on the notion that if a system can gather useful information about the user, generate a relevant user model and apply it appropriately, it would be possible to adapt the behavior of a system and its interface to the user at the individual level. Personal-ization of a user interface features can enhance usability. With recent technological advances, personalization can be achieved automatically and unobtrusively. A user interface can deploy a NeuroIS technology such as eye-tracking that learns from the user's visual behavior to provide users an experience most unique to them. The advantage of eye-tracking technology is that subjects cannot consciously manipulate their responses since they are not readily subject to manipulation. The objective of this dissertation is to develop a theoretical framework for user personalization during reading comprehension tasks based on two machine learning (ML) models. The proposed ML-based profiling process consists of user's age characterization and user's cognitive load detection, while the user reads text. To this end, detection of cognitive load through eye-movement features was investigated during different cognitive tasks (see Chapters 3, 4 and 6) with different task conditions. Furthermore, in separate studies (see Chapters 5 and 6) the relationship between user's eye-movements and their age population (e.g., younger and older generations) were carried out during a reading comprehension task. A Tobii X300 eye tracking device was used to record the eye movement data for all studies. Eye-movement data was acquired via Tobii eye tracking software, and then preprocessed and analyzed in R for the aforementioned studies. Machine learning techniques were used to build predictive models. The aggregated results of the studies indicate that machine learning accompanied with a NeuroIS tool like eye-tracking, can be used to model user characteristics like age and user mental states like cognitive load, automatically and implicitly with accuracy above chance (range of 70-92%). The results of this dissertation can be used in a more general framework to adaptively modify content to better serve the users mental and age needs. Text simplification and modification techniques might be developed to be used in various scenarios.

Nous sommes de plus en plus nombreux, jeunes ou âgés, à travailler devant un écran en milieu professionnel. Cette activité de travail peut induire une charge mentale et une fatigue importante, qui peuvent à leur tour générer, chez les personnes âgées notamment, des problèmes de santé. Dans ce contexte, il est donc important de développer et de déployer des solutions de surveillance de l’état psychophysiologique et d’alerte du travailleur sur écran.La charge mentale et la fatigue sont des phénomènes psychophysiologiques multidimensionnels. Des routines de travail inappropriées sont susceptibles d’accélèrr le développement de la fatigue, qui peut s’accompagner d’une diminution des ressources cognitives disponibles et d’une augmentation des erreurs. Les micro-pauses font partie des solutions possibles pour retarder, si elles sont mises en place de manière appropriée, l’apparition de la fatigue et de ses effets corollaires. L'oculométrie est une technologie prometteuse permettant la quantification de la charge mentale et des niveaux de fatigue. Ce travail doctoral avait pour objectif principal d’évaluer si, et dans quelle mesure, l'oculométrie, en association avec la charge mentale et la fatigue, peut être utilisée comme outil de détection précoce de la fatigue, et comme moyen de paramétrage de micro-pauses à mettre en œuvre afin de ralentir et/retarder le développement de la fatigue durant l’exécution d’un travail sur ordinateur.Pour répondre à cet objectif, trois études (I-III) portant sur 58 individus jeunes et âgés ont été conduites. Une tâche expérimentale, se rapprochant de celle qu’uin travailleur peut réaliser sur ordinateur, a été développée pour induire une charge mentale de trois niveaux d’intensités croissantes. Les positions du regard et les réponses pupillaires ont été enregistrées pendant l'exécution de cette tâche afin de détecter les événements oculaires et de calculer ainsi les paramètres oculomoteurs tels que la durée de fixation par exemple.Dans l'étude I, cette tâche a été effectuée à deux jours d’intervalle et dans un ordre contrebalancé. Les performances à la tâche et la charge de travail ont d’une part été mesurées. Dix-neuf paramètres oculomoteurs ont, d’autre part, été calculés pour évaluer leur sensibilité à la charge mentale, et leur fiabilité sur plusieurs jours.Dans l'étude II, le développement de la fatigue a été étudié au moyen des mesures oculométriques au cours de l'exécution de la tâche pendant 40 minutes, alors que les mesures de la fatigue subjective et de la performance ont été acquises. Un modèle prédictif du développement de la fatigue a été conçu sur la base des données d’oculomotricité recueillies dans l'étude II. Un système de biofeedback en temps réel basé sur l'oculométrie a été mis en œuvre. Son principe de fonctionnement repose sur la détection de la fatigue à l'aide du modèle développé, et le déclenchement de micro-pauses dès lors qu’un état de fatigue est détecté, afin de ralentir sa progression durant l’exécution de la tâche. L'efficacité et la robustesse de ce système de contrôle en boucle fermée ont été comparées à des micro-pauses déclenchées de manière automatique en termes de charge de travail perçue et de précision de la détection de la fatigue sur toute la journée.Nos résultats ont mis en évidence la fiabilité et la sensibilité d’un ensemble de paramètres oculomoteurs permettant d’estimer la charge mentale et la fatigue chez les personnes jeunes et âgées. Le biofeedback basé sur l’oculométrie a permis la planification des micro-pauses, qui, en comparaison à des micro-pauses déclenchées de manière automatique, ont réduit de manière significative la charge de travail perçue et le développement de la fatigue.Dans leur ensemble, les résultats suggèrent que le système de biofeedback oculométrique développé dans le cadre de ce travail doctoral peut représenter une solution prometteuse pouvant contribuer à un travail sur ordinateur productif et sain. / Computer work, as a prevalent occupation, involves different levels of mental load and fatigue with possible negative health effects. The population aging has also led to increased elderly workers highlighting the need for protective measures.Mental load and fatigue are multidimensional psychophysiological phenomena. Inefficient work routines accelerate fatigue development, associated with declined cognitive resources and increased errors. Micro-breaks are strategic solutions to counteract fatigue subject to design constraints, e.g. timing plan. Eye tracking is a promising technology for the quantification of mental load and fatigue levels. The oculometrics were aimed to be studied in association with age, mental load and fatigue, allowing early detection of fatigue, and thereby applying biologically-valid micro-breaks to decelerate fatigue development.Upon this, three Studies (I-III) involving 58 young and elderly individuals were conducted. A task, resembling computer work, was developed to induce mental load. Gaze positions and pupillary responses were recorded during the task execution to detect ocular events (saccades, fixations, and blinks), and thereby computing oculometrics e.g. fixation duration. In Study I, the task was performed on three load levels in a counterbalanced order across two days. Between-day reliability and mental-load sensitivity of 19 oculometrics were assessed, besides measuring performance and perceived workload. In Study II, fatigue development was explored in oculometrics during 40-min performance of the task while subjective fatigue and performance metrics were obtained. A predictive model of fatigue was developed in Study III based on the ocular data collected in Study II. An oculometrics-based biofeedback system was implemented in real time to detect fatigue using the developed model, which triggered micro-breaks upon fatigue detections to counteract it during the task. The optimality of the system was compared with self-triggering micro-breaks in terms of fatigue trends and workload.A group of oculometrics was sensitive and reliable to reflect mental load and fatigue in the young and elderly individuals. Similar trends in the oculometrics were observed with increased mental load and fatigue levels, implying shared neural systems for both conditions. Although age-related differences were exhibited in some oculometrics, age did not directly contribute to the predictive model of fatigue. The oculometrics-based biofeedback provided an improved solution for timing plan of micro-breaks in reducing workload and fatigue development compared with self-triggering micro-breaks. The oculometrics-biofeedback system made a benchmark towards productive and healthy computer work.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第18322号 / 農博第2047号 / 新制||農||1021(附属図書館) / 学位論文||H26||N4829(農学部図書室) / 31180 / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 近藤 直, 教授 松井 徹, 准教授 小川 雄一 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

No description available.

An early detection of hearing loss in children is important for the child's speech and language development. For children between 3-6 months, a reliable method to measure hearing and determine hearing thresholds is missing. A hearing test based on the pupillary response to auditory signal detection as measured by eye tracking is based on an automatic physiological response. This hearing test could be used instead of the objective hearing tests used today. The presence of pupillary response has been shown in response to speech, but it is unstudied in response to sinus tones. The objective of this thesis was to study whether there is a consistent pupillary response to different sinus tone frequencies commonly used in hearing tests and if yes, to determine reliably the time window of this response. Four different tests were done. The adult pupillary response in regard to sinus tone stimuli with four frequency levels (500 Hz, 1000 Hz, 2000 Hz and 4000 Hz), and four loudness levels (silence, 30 dB, 50 dB and 70 dB) was tested (N=20, 15 females, 5 males). Different brightness levels and distractions on the eye tracking screen were investigated in three substudies (N=5, 4 females, 1 male). Differences between silence and loudness levels within frequency levels were tested for statistical significance. A pupillary response in regard to sinus tones occurred consistently between 300 ms and 2000 ms with individual variation, i.e. earlier than for speech sounds. Differences between silence and loudness levels were only statistically significant for 4000 Hz. No statistical difference was shown between different brightness levels or if there were distractions present on the eye tracker screen. The conclusion is that pupillary response to pure sinus tones in adults is a possible measure of hearing threshold for at least 4000 Hz. Larger studies are needed to confirm this, and also to more thoroughly investigate the other frequencies. / En tidig upptäckt av hörselnedsättning hos barn är viktig för barnets tal- och språkutveckling. För barn mellan 3-6 månader saknas det en tillförlitlig metod för att mäta hörsel och bestämma hörtrösklar. Ett hörseltest baserad på pupillreaktion på ljud som mäts med en eye tracker bygger på en automatisk fysiologisk reaktion och skulle kunna användas istället för de objektiva test som används idag. Hitintills har pupillreaktion på tal påvisats, men det saknas studier som studerat eventuella reaktioner på sinustoner. Syftet med denna uppsats var att undersöka om det finns en enhetlig pupillreaktion på de olika frekvenserna av sinustoner som vanligen används i hörseltest. Vidare var studiens syfte att fastställa ett tillförlitligt tidsfönster för pupillreaktion. Fyra olika typer av tester utfördes. Pupillreaktionen mot sinustoner med fyra olika frekvensnivåer (500 Hz, 1000 Hz, 2000 Hz och 4000 Hz), och fyra olika ljudnivåer (tystnad, 30 dB, 50 dB och 70 dB) undersöktes i ett test på vuxna deltagare (N=20, 15 kvinnor, 5 män). Olika ljusnivåer och distraktioner på eye tracker-skärmen undersöktes i tre test (N=5, 4 kvinnor, 1 man). Skillnaderna mellan ljudnivåer och frekvensnivåer testades med statistiska tester. Resultaten visade att pupillreaktion på sinustoner inträffade konsekvent mellan 300 ms och 2000 ms med individuella variationer. Denna reaktionstid inträffar tidigare än för taljud. En statistisk signifikant skillnad mellan tystnad och olika ljudnivåer kunde endast ses för frekvensnivån 4000 Hz. Ingen statistisk skillnad uppmättes mellan olika ljudnivåer eller om det fanns distraktioner på eye tracker-skärmen. De i studien framkomna resultaten tyder på att pupillreaktioner mot rena sinustoner hos vuxna är en möjlig metod för att identifiera hörseltrösklar för åtminstone 4000 Hz. Större studier behöver göras för att fastställa detta och en noggrannare undersökning behöver genomföras för de andra frekvenserna.

With no online pupillary analysis methods today, both the medical and the research fields are left to carry out a lengthy, manual and often faulty examination. A real-time, intelligent, embedded systems solution to pupillary analysis would help reduce faulty diagnosis, speed-up the analysis procedure by eliminating the human expert operator and in general, provide a versatile and highly adaptable research tool. Therefore, this thesis has sought to investigate, develop and test possible system designs for pupillary analysis, with the aim for caffeine detection. A pair of LED manipulator glasses have been designed to standardize the illumination method across testing. A data analysis method of the raw pupillary data has been established offline and then adapted to a real-time platform. ANN was chosen as classification algorithm. The accuracy of the ANN from the offline analysis was 94% while for the online classification the obtained accuracy was 17%. A realtime data communication and synchronization method has been developed. The resulting system showed reliable and fast execution times. Data analysis and classification took no longer than 2ms, faulty data detection showed consistent results. Data communication suffered no message loss. In conclusion, it is reported that a real-time, intelligent, embedded solution is feasible for pupillary analysis.