Thesis (MSc. (Human Physiology, Faculty of Health Sciences))--University of Pretoria, 2008. / Summary in English. Includes bibliographical references.

Diss. (sammanfattning) Linköping : Univ., 2004. / Härtill 5 uppsatser.

Tesis por compendio / [ES] Comprender el comportamiento humano en situaciones de riesgo, cómo los factores individuales y externos influyen en nuestras decisiones y en qué medida es posible influir y modificar nuestros comportamientos, constituye un desafío tanto para los científicos como para la sociedad en general. Desde la perspectiva de la Seguridad y Salud en el Trabajo (SST), así como en numerosos campos como la sociología y las finanzas, este tema tiene importantes implicaciones ya que las situaciones de riesgo son un aspecto común en diversos ámbitos de nuestra vida. La toma de riesgos (TR) es parte del proceso de toma de decisiones en situaciones de incertidumbre, en las que se conoce de antemano la probabilidad de cada consecuencia positiva o negativa. Si bien el concepto de la TR está bien definido en la literatura, se ha abordado desde diferentes perspectivas, por lo que los factores que se han propuesto para explicar o moderar la TR también son muy diversos. Centrándonos en los factores individuales (procesos cognitivos y emocionales) que influyen en la TR, estos pueden afectar la forma en que se abordan las situaciones peligrosas de dos maneras diferentes. En primer lugar, pueden sesgar la percepción de una situación, de modo que no se lleve a cabo una evaluación adecuada y por tanto esto lleve a conductas sesgadas. En segundo lugar, estos factores configuran una cierta propensión general al riesgo en los seres humanos, de modo que pueden o no sentirse atraídos por situaciones potencialmente peligrosas. De la misma manera que la definición de la TR se ha abordado desde diferentes perspectivas, su evaluación también se ha tratado desde diferentes puntos de vista y constituye hoy en día un desafío para investigadores y profesionales, por lo que no se ha encontrado un consenso claro en cuanto a la existencia de una medida validada para la TR. La evaluación de la TR se ha realizado tradicionalmente mediante cuestionarios; sin embargo, se ha demostrado que estas medidas presentan diversas limitaciones que pueden conducir a resultados alterados. Las tareas comportamentales surgen como una solución alternativa capaz de superar algunas de estas barreras. En cambio, su capacidad de transferencia a situaciones de la vida real parece ser limitada. La realidad virtual (RV) permite recrear situaciones reales simuladas para realizar evaluaciones basadas en el desempeño. La RV presenta numerosas ventajas que pueden aportar beneficios para la evaluación de los comportamientos humanos, ya que aporta una mayor inmersión, fidelidad y un mayor nivel de implicación que los métodos de evaluación tradicionales, y numerosos trabajos en el campo de la psicología aplicada y la neurociencia organizacional han avalado su uso para evaluación humana. En esta investigación, proponemos la RV como tecnología capaz de facilitar el estudio de los procesos de la TR, aprovechando sus numerosas posibilidades, que se pueden resumir como: simulación de situaciones de riesgo realistas, interacciones naturales con el entorno virtual, inclusión de medidas implícitas para evaluación oculta y medición fisiológica en tiempo real. Esta tesis proporciona aportaciones a la definición de la TR, particularmente en la identificación de qué factores constituyen este complejo proceso. Además, investiga el uso de la RV inmersiva en la investigación del comportamiento humano, específicamente para la evaluación de la TR, proporcionando premisas de diseño de entornos virtuales para la evaluación de los constructos psicológicos identificados como determinantes para definir la TR. Finalmente, analiza la validez de la RV en combinación con medidas fisiológicas para la evaluación de la TR de forma implícita. / [CA] Comprendre el comportament humà en situacions de risc, com els factors individuals i externs influeixen en les nostres decisions i en quina mesura és possible influir i modificar els nostres comportaments, constitueix un desafiament tant per als científics com per a la societat en general. Des de la perspectiva de la Seguretat i Salut en el Treball (SST), així com en nombrosos camps com la sociologia i les finances, aquest tema té importants implicacions ja que les situacions de risc són un aspecte comú en diversos àmbits de la nostra vida. La presa de riscos (PR) és part del procés de presa de decisions en situacions d'incertesa, en les quals es coneix per endavant la probabilitat de cada conseqüència positiva o negativa. Si bé el concepte de la PR està ben definit en la literatura, s'ha abordat des de diferents perspectives, per la qual cosa els factors que s'han proposat per a explicar o moderar la PR també són molt diversos. Centrant-nos en els factors individuals (processos cognitius i emocionals) que influeixen en la PR, aquests poden afectar la forma en què s'aborden les situacions perilloses de dues maneres diferents. En primer lloc, poden esbiaixar la percepció d'una situació, de manera que no es duga a terme una avaluació adequada i per tant això porte a conductes esbiaixades. En segon lloc, aquests factors configuren una certa propensió general al risc en els éssers humans, de manera que poden o no sentir-se atrets per situacions potencialment perilloses. De la mateixa manera que la definició de la PR s'ha abordat des de diferents perspectives, la seua avaluació també s'ha tractat des de diferents punts de vista i constitueix hui dia un desafiament per a investigadors i professionals, per la qual cosa no s'ha trobat un consens clar quant a l'existència d'una mesura validada per a la PR. L'avaluació de la PR s'ha realitzat tradicionalment mitjançant qüestionaris; no obstant això, s'ha demostrat que aquestes mesures presenten diverses limitacions que poden conduir a resultats alterats. Les tasques comportamentals sorgeixen com una solució alternativa capaç de superar algunes d'aquestes barreres. En canvi, la seua capacitat de transferència a situacions de la vida real sembla ser limitada. La realitat virtual (RV) permet recrear situacions reals simulades per a realitzar avaluacions basades en l'acompliment. La RV presenta nombrosos avantatges que poden aportar beneficis per a l'avaluació dels comportaments humans, ja que aporta una major immersió, fidelitat i un major nivell d'implicació que els mètodes d'avaluació tradicionals, i nombrosos treballs en el camp de la psicologia aplicada i la neurociència organitzacional han avalat el seu ús per a avaluació humana. En aquesta investigació, proposem la RV com a tecnologia capaç de facilitar l'estudi dels processos de la PR, aprofitant les seues nombroses possibilitats, que es poden resumir com: simulació de situacions de risc realistes, interaccions naturals amb l'entorn virtual, inclusió de mesures implícites per a avaluació oculta i mesurament fisiològic en temps real. Aquesta tesi proporciona aportacions a la definició de la PR, particularment en la identificació de quins factors constitueixen aquest complex procés. A més, investiga l'ús de la RV immersiva en la investigació del comportament humà, específicament per a l'avaluació de la PR, proporcionant premisses de disseny d'entorns virtuals per a l'avaluació dels constructes psicològics identificats com a determinants per a definir la PR. Finalment, analitza la validesa de la RV en combinació amb mesures fisiològiques per a l'avaluació de la PR de manera implícita. / [EN] Understanding human behaviour in risk situations, how individual and external factors influence our decisions and to what extent it is possible to influence and modify our behaviours, constitutes a challenge both for scientists and for society in general. From the perspective of Occupational Safety and Health (OSH), as well as in numerous fields such as sociology of finance, this topic has important implications since risk situations are a common aspect in various domains of our lives. Risk taking (RT) is part of the decision-making process in uncertain situations, in which the probability of each positive or negative consequence is known in advance. Although the concept of RT is well defined in the literature, it has been approached from different perspectives, so that the factors that have been proposed to explain or moderate RT are also very diverse. Focusing on the individual factors - cognitive and emotional processes - that influence RT, these may affect how hazardous situations are addressed in two different ways. First, they can skew the perception of a situation, so that an adequate evaluation is not carried out and therefore this leads to biased behaviors. Second, these factors shape a certain general propensity towards risk in humans, so that they may or may not be attracted to potentially dangerous situations. In the same way that the definition of RT has been approached from different perspectives, the evaluation of RT has also been treated from different points of view and nowadays constitutes a challenge for researchers and practitioners, so that a clear consensus has not been found regarding the existence of a validated measure for RT. RT evaluation has traditionally been carried out using questionnaires; however, it has been demonstrated that these measures present various limitations that can lead to altered results. Behavioural tasks emerge as an alternative solution capable of overcoming some of these boundaries. Instead, their ability to transference to real life situations appears to be limited. Virtual reality (VR) enables recreating real-simulated situations to carry out performance-based assessments. VR presents numerous advantages that can provide benefits for the evaluation of human behaviours, since it provides greater immersion, fidelity and a higher level of involvement than traditional evaluation methods, and numerous works in the field of applied psychology and organizational neuroscience have endorsed its use for human assessment. In this investigation, we propose VR as technology capable of facilitating the study of RT processes, taking advantage of its numerous possibilities, which can be resumed as: simulation of realistic risk situations, natural interactions with the virtual environment, inclusion of implicit measures for stealth assessment and physiological real-time measurement. This thesis provides novel contributions to the definition of RT, particularly in the identification of which factors constitute this complex process. Moreover, it investigates the use of immersive VR in human behaviour research, specifically for RT assessment, providing design premises of virtual environments for the evaluation of the psychological constructs identified as determinants to define RT. Finally, it analyses the validity of VR in combination with physiological measures for the evaluation of RT in an implicit way. / Contrato predoctoral FPI (BES-2017-079857). Ministerio de Economía, Industria y Competitividad (Madrid, Spain). / Juan Ripoll, CD. (2021). Virtual reality environments for the study of decision-making processes in risky contexts through the use of physiological measures and behavioural responses [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/171236 / Compendio

Hansen and Hansen (1988) found that angry targets in happy crowds were found more quickly and accurately than happy targets in angry crowds. This finding, they dubbed the Face-in-the-Crowd effect. Gilboa-Schechtman and colleagues (1999) found that high anxious participants show a greater enhancement of detecting angry versus happy targets. The purpose of the current studies was to replicate these findings, and to determine whether Rational and Experiential decision-making styles play a role in target detection (Study One) and crowd searching (Study Two), and if these decision-making styles interact with affective predisposition for both reaction time and galvanic skin response in the face-in-the-crowd task. In Study One, I replicated the anger superiority effect and the Anxiety x Target interaction. I also found that the Rational Group tended to be faster than the Experiential Group overall. I found that the High Trait Anxious group had higher GSR than the Low Trait Anxious group averaged over both target conditions. The Rational group had higher GSR when presented with happy targets than when presented with angry targets whereas the Experiential group did not show this difference. In Study Two, I failed to replicate the anger inferiority effect of crowd searching, but I did find that the Rational group tended to be faster than the Experiential group, especially for angry crowd searching. I also found that the Low-State-Anxious-Rational group had lower galvanic skin responses than all other groups across all analyses. The most exciting finding of these two studies was that he Rational Group demonstrated a facility for the face-in-the-crowd task, validating decision-making style as an important dimension to be considered in future face-in-the-crowd research. The research also provided support for network theories and it is hoped that future studies might endeavor to explore facial processing with this theoretical framework in mind.

Hansen and Hansen (1988) found that angry targets in happy crowds were found more quickly and accurately than happy targets in angry crowds. This finding, they dubbed the Face-in-the-Crowd effect. Gilboa-Schechtman and colleagues (1999) found that high anxious participants show a greater enhancement of detecting angry versus happy targets. The purpose of the current studies was to replicate these findings, and to determine whether Rational and Experiential decision-making styles play a role in target detection (Study One) and crowd searching (Study Two), and if these decision-making styles interact with affective predisposition for both reaction time and galvanic skin response in the face-in-the-crowd task. In Study One, I replicated the anger superiority effect and the Anxiety x Target interaction. I also found that the Rational Group tended to be faster than the Experiential Group overall. I found that the High Trait Anxious group had higher GSR than the Low Trait Anxious group averaged over both target conditions. The Rational group had higher GSR when presented with happy targets than when presented with angry targets whereas the Experiential group did not show this difference. In Study Two, I failed to replicate the anger inferiority effect of crowd searching, but I did find that the Rational group tended to be faster than the Experiential group, especially for angry crowd searching. I also found that the Low-State-Anxious-Rational group had lower galvanic skin responses than all other groups across all analyses. The most exciting finding of these two studies was that he Rational Group demonstrated a facility for the face-in-the-crowd task, validating decision-making style as an important dimension to be considered in future face-in-the-crowd research. The research also provided support for network theories and it is hoped that future studies might endeavor to explore facial processing with this theoretical framework in mind.

Simulation-based training has gained widespread attention recently as a response to drawbacks associated with traditional training approaches, such as high training costs (instructors, equipment, etc.), high risks (e.g. pilot training), and ethical issues (e.g. medical training), as well as a lack of availability of certain training environments (e.g. space exploration). Apart from their target training domains, many of aspects of simulations differ, such as their degree of physical realism (fidelity), scenarios (e.g. story), and pedagogical aspects (e.g. after-action reviews and collaborative learning). Among those aspects, designers have mostly focused on developing high-fidelity simulations with the expectation of increasing the effectiveness of training. However, some authors suggest that the above belief is a myth as researchers have failed to identify a linear relationship between the (physical) fidelity and training effectiveness of simulations.  Most researchers have therefore evaluated the correspondence between the behaviours of trainees in both real world and simulated contexts, however, the existing methods of simulation validation using behavioural measures have a number of drawbacks, such as the fact that they do not address certain complex phenomena of skills acquisition. Bridging the above knowledge gap, this research reports on empirical investigations using an improved methodology for validating training simulations. This research includes an investigation of the user experience of trainees, with respect to the acceptance of virtual scenarios provoking a similar psychophysiological response as in real world scenarios, and the training potential of simulations with respect to the positive transfer of training from a simulator to real world operational contexts. The most prominent features of the proposed methodology include the use of psychophysiological measures in addition to traditional behavioural measures and the use of natural (quasi-) experiments. Moreover, its conceptual framework was influenced by contemporary theories in cognitive science (e.g. constructivism and embodied cognition). The results of this research have several important theoretical and methodological implications, involving, for example, the dependency of the effectiveness of simulations on the perceived realism of trainees, which is more embodied than has been predicted by previous researchers, and the requirement of several different types/levels of adaptive training experience, depending on the type of trainee. / Träning i simulatorer har på senare år fått ökad uppmärksamhet som en respons på problem och svårigheter förknippade med traditionella träningsansatser, såsom höga kostnader (instruktörer och utrustning, etc.), hög risk (t.ex. träning av piloter), och etiska aspekter (t.ex. träning av kirurger), likaväl som avsaknaden av träningsmöjligheter och miljöer (t.ex. forskning om rymden). Bortsett från vad som specifikt tränas så skiljer sig simuleringar åt i ett flertal olika aspekter såsom fysisk realism (eng. fidelity), scenarier (handling) och pedagogiska aspekter (t.ex. genomgång efter övning och kollaborativt lärande).  Bland dessa aspekter så har designers ofta fokuserat att utveckla simuleringar med hög realism med förväntningen att detta ska göra träningen mer effektiv. Litteraturen antyder dock att denna föreställning inte stämmer och att de flesta simuleringar med hög realism inte har lyckats uppnå denna målsättning. En slutsats är därför att det finns ett behov av metoder som kan validera potentialen hos simuleringar avsedda att stödja träning – redan innan dessa används. Enligt litteraturen så är utbildningspotentialen hos en simulering starkt kopplad till hur väl den psykologiska effekten en simulering har, stämmer överens med en verklig upplevelse. Forskning har emellertid identifierat ett flertal svagheter hos existerande ansatser för att validera simuleringar; de är oftast baserade på prestations- och/eller subjektiva mätningar; de har fokuserat en eller ett fåtal psykologiska aspekter; och de bygger på traditionella teorier. Baserat på resultat från studier av en kör-simulator presenteras och föreslås i denna avhandling ett förbättrat ramverk för utvärdering. De mest centrala egenskaperna hos det föreslagna ramverket inbegriper användandet av psyko-fysiologiska mått tillsammans med mer traditionella mått; det konceptuella ramverket bygger på samtida teoretiska ansatser (tex konstruktivism och kroppslig kognition); samt användandet av fält (kvasi-) experiment. Utöver uppnåendet av uppsatta mål för forskningen så har resultaten ett flertal teoretiska och metodologiska implikationer. Bland dessa återfinns beroendet mellan effektiviteten hos en simulering och den upplevelse av realitet som de tränade har, vilken är mer grundläggande än vad som rapporterats i tidigare forskning, samt kravet på flera och olika typer av anpassning av träningsupplevelse för den tränade för att förhöja potentialen hos träningssimulatorer. / SIDA Funded National e-Learning Centre Project at the University of Colombo School of Computing, Sri Lanka

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.

No description available.

The use of autonomous robots in our society is increasing every day and a robot is no longer seen as a tool but as a team member. The robots are now working side by side with us and provide assistance during dangerous operations where humans otherwise are at risk. This development has in turn increased the need of robots with more human-awareness. Therefore, this master thesis aims at contributing to the enhancement of human-aware robotics. Specifically, we are investigating the possibilities of equipping autonomous robots with the capability of assessing and detecting activities in human teams. This capability could, for instance, be used in the robot's reasoning and planning components to create better plans that ultimately would result in improved human-robot teamwork performance. we propose to improve existing teamwork activity recognizers by adding intangible features, such as stress, motivation and focus, originating from human behavior models. Hidden markov models have earlier been proven very efficient for activity recognition and have therefore been utilized in this work as a method for classification of behaviors. In order for a robot to provide effective assistance to a human team it must not only consider spatio-temporal parameters for team members but also the psychological.To assess psychological parameters this master thesis suggests to use the body signals of team members. Body signals such as heart rate and skin conductance. Combined with the body signals we investigate the possibility of using System Dynamics models to interpret the current psychological states of the human team members, thus enhancing the human-awareness of a robot. / Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot. / <p>The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.</p>