Navigation and interaction in a real-scale digital mock-up using natural language and user gesture

This paper tries to demonstrate a very new real-scale 3D system and sum up some firsthand and cutting edge results concerning multi-modal navigation and interaction interfaces. This work is part of the CALLISTO-SARI collaborative project. It aims at constructing an immersive room, developing a set of software tools and some navigation/interaction interfaces. Two sets of interfaces will be introduced here: 1) interaction devices, 2) natural language (speech processing) and user gesture. The survey on this system using subjective observation (Simulator Sickness Questionnaire, SSQ) and objective measurements (Center of Gravity, COG) shows that using natural languages and gesture-based interfaces induced less cyber-sickness comparing to device-based interfaces. Therefore, gesture-based is more efficient than device-based interfaces.FUI CALLISTO-SAR

A Classification Model for Sensing Human Trust in Machines Using EEG and GSR

Today, intelligent machines \emph{interact and collaborate} with humans in a way that demands a greater level of trust between human and machine. A first step towards building intelligent machines that are capable of building and maintaining trust with humans is the design of a sensor that will enable machines to estimate human trust level in real-time. In this paper, two approaches for developing classifier-based empirical trust sensor models are presented that specifically use electroencephalography (EEG) and galvanic skin response (GSR) measurements. Human subject data collected from 45 participants is used for feature extraction, feature selection, classifier training, and model validation. The first approach considers a general set of psychophysiological features across all participants as the input variables and trains a classifier-based model for each participant, resulting in a trust sensor model based on the general feature set (i.e., a "general trust sensor model"). The second approach considers a customized feature set for each individual and trains a classifier-based model using that feature set, resulting in improved mean accuracy but at the expense of an increase in training time. This work represents the first use of real-time psychophysiological measurements for the development of a human trust sensor. Implications of the work, in the context of trust management algorithm design for intelligent machines, are also discussed.Comment: 20 page

The influence of affective factors on time perception

Several studies have suggested that both affective valence and arousal affect the perception of time. How-ever, in previous experiments these two affective dimensions were not systematically controlled. In the present study, a set of emotional slides rated for valence and arousal (International Affective Picture System) were projected to two groups of subjects for 2, 4 and 6 sec. One group estimated the duration on an analog scale and a second group reproduced the interval by pushing a button. Heart rate and skin conductance responses were also recorded. A highly significant valence by arousal interaction affected duration judg-ments. For low arousal stimuli, the duration of negative slides was judged relatively shorter than the duration of positive slides. For high arousal stimuli, the duration of negative slides was judged longer than the dura-tion of positive slides. These results are interpreted within a model of action tendency, in which the level of arousal controls two different motivational mechanisms, one emotional and the other attentional

Influence of Task Combination on EEG Spectrum Modulation for Driver Workload Estimation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Objective: This study investigates the feasibility of using a method based on electroencephalography (EEG) for deriving a driver’s mental workload index. Background: The psychophysiological signals provide sensitive information for human functional states assessment in both laboratory and real-world settings and for building a new communication channel between driver and vehicle that allows for driver workload monitoring. Methods: An experiment combining a lane-change task and n-back task was conducted. The task load levels were manipulated in two dimensions, driving task load and working memory load, with each containing three task load conditions. Results: The frontal theta activity showed significant increases in the working memory load dimension, but differences were not found with the driving task load dimension. However, significant decreases in parietal alpha activity were found when the task load was increased in both dimensions. Task-related differences were also found. The driving task load contributed more to the changes in alpha power, whereas the working memory load contributed more to the changes in theta power. Additionally, these two task load dimensions caused significant interactive effects on both theta and alpha power. Conclusion: These results indicate that EEG technology can provide sensitive information for driver workload detection even if the sensitivities of different EEG parameters tend to be task dependent. Application: One potential future application of this study is to establish a general driver workload estimator that uses EEG signals

Exploring Cognitive States: Methods for Detecting Physiological Temporal Fingerprints

Cognitive state detection and its relationship to observable physiologically telemetry has been utilized for many human-machine and human-cybernetic applications. This paper aims at understanding and addressing if there are unique psychophysiological patterns over time, a physiological temporal fingerprint, that is associated with specific cognitive states. This preliminary work involves commercial airline pilots completing experimental benchmark task inductions of three cognitive states: 1) Channelized Attention (CA); 2) High Workload (HW); and 3) Low Workload (LW). We approach this objective by modeling these "fingerprints" through the use of Hidden Markov Models and Entropy analysis to evaluate if the transitions over time are complex or rhythmic/predictable by nature. Our results indicate that cognitive states do have unique complexity of physiological sequences that are statistically different from other cognitive states. More specifically, CA has a significantly higher temporal psychophysiological complexity than HW and LW in EEG and ECG telemetry signals. With regards to respiration telemetry, CA has a lower temporal psychophysiological complexity than HW and LW. Through our preliminary work, addressing this unique underpinning can inform whether these underlying dynamics can be utilized to understand how humans transition between cognitive states and for improved detection of cognitive states

Evaluating Respiratory Sinus Arrhythmia as a Mediator of Relations between Minority Stress and Depressive Symptoms Among Sexual Minorities

Compared with heterosexuals, those with sexual minority identities (e.g., lesbian, gay, bisexual) are at significantly greater risk of psychopathology, including depression—the most common mental health disorder in the general population. A large body of research suggests that disparities in depression between heterosexuals and sexual minority groups are due, at least in part, to minority stress. Minority stress includes stressors unique to minority groups, such as marginalization and discrimination based on race or sexual identity. To date, most work demonstrating associations between minority stress and depression has used retrospective self- reports of minority stress exposure, so little is known about acute effects of minority stress exposure on physiological functions. In this study, I examine the potential moderating or mediating effect of respiratory sinus arrhythmia (RSA)—the high frequency component of heart rate variability associated with breathing—on associations between minority stress and symptoms of depression. Heterosexual (n = 43; 62.5% women) and sexual minority (n = 24; 59.3% women) college students viewed films designed to induce minority stress and completed the Beck Depression Inventory (BDI-II). Results indicated no differences in RSA reactivity or BDI scores between heterosexuals and sexual minority group members.No embargoAcademic Major: Psycholog

Selecting films for sex research: Gender differences in erotic film preference

The official published version can be obtained from the link below.The aim of this study was to explore gender differences in sexual responsiveness to erotic films that had been selected for their differential appeal for men and women. A secondary objective was to identify variables that influence sexual arousal and explore whether these variables differ for men and women. Fifteen men (M age = 26 yrs) and 17 women (M age = 24 yrs) were presented with 20 film clips depicting heterosexual interactions, half of which were female- and the other half male-selected, and were asked to rate the clips on a number of dimensions. Overall, men found the film clips more sexually arousing than did the women. Gender differences in arousal were negligible for female-selected clips but substantial for male-selected clips. Furthermore, men and women experienced higher levels of sexual arousal to clips selected for individuals of their own gender. Cluster regression analyses, explaining 77% of the variance for male and 65% for female participants, revealed that men's sexual arousal was dependent upon the attractiveness of the female actor, feeling interested, and both imagining oneself as a participant and watching as an observer. For women, with all variables entered, only imagining oneself as a participant contributed to sexual arousal ratings. The findings suggest that how films are selected in sex research is an important variable in predicting levels of sexual arousal reported by men and women

Spontaneous blink rate as an index of attention and emotion during film clips viewing

Spontaneous blinking is a non-invasive indicator known to reflect dopaminergic influence over frontal cortex and attention allocation in perceptual tasks. 38 participants watched eighteen short film clips (2 min), designed to elicit specific affective states, and arranged in six different emotional categories, while their eye movements were recorded from the vertical electroculogram. The largest blink rate inhibition, reflecting greater attention allocation to the movie, was observed during the presentation of Erotic clips, excerpts on wilderness depicting beautiful landscapes (Scenery), as well as clips showing crying characters (Compassion). Instead, the minimum blink rate inhibition was found for Fear clips, which induced a defensive response with stimulus rejection. Blink rate across time evidenced how Compassion clips elicited early inhibition while Sadness clips induced a slower, later inhibition. Correlation analyses also revealed a negative correlation (r < -0.40) between total blink rate recorded during Erotic and Compassion clips and self-reported interest. Overall, the main variable explaining blink rate was emotional Valence. Results suggest that blink modulation is related with the motivational relevance and biological significance of the stimuli, tracking their differential recruitment of attentional resources. Furthermore, they provide a solid background for studying the emotion-attention patterns and their deficits also in clinical samples (e.g., neurological and psychiatric patients) using spontaneous blinking as a not-interfering psychophysiological measure

My heart is racing! Psychophysiological dynamics of skilled racecar drivers

Our purpose was to test the multi-action plan (MAP) model assumptions in which athletes’ psychophysiological patterns differ among optimal and suboptimal performance experiences. Nine professional drivers competing in premier race categories (e.g., Formula 3, Porsche GT3 Cup Challenge) completed the study. Data collection involved monitoring the drivers’ perceived hedonic tone, accuracy on core components of action, posture, skin temperature, respiration rate, and heart rate responses during a 40-lap simulated race. Time marks, gathered at three standardized sectors, served as the performance variable. The A1GP racing simulator (Allinsport, Modena) established a realistic race platform. Specifically, the Barcelona track was chosen due to its inherently difficult nature characterized by intermittent deceleration points. Idiosyncratic analyses showed large individual differences in the drivers’ psychophysiological profile, as well as distinct patterns in regards to optimal and suboptimal performance experiences. Limitations and future research avenues are discussed. Action (e.g., attentional control) and emotion (e.g., biofeedback training) centered applied sport psychology implications are advanced

Interactions between empathy and resting heart rate in early adolescence predict violent behavior in late adolescence and early adulthood.

BackgroundAlthough resting heart rate (RHR) and empathy are independently and negatively associated with violent behavior, relatively little is known about the interplay between these psychophysiological and temperament-related risk factors.MethodsUsing a sample of 160 low-income, racially diverse men followed prospectively from infancy through early adulthood, this study examined whether RHR and empathy during early adolescence independently and interactively predict violent behavior and related correlates in late adolescence and early adulthood.ResultsControlling for child ethnicity, family income, and child antisocial behavior at age 12, empathy inversely predicted moral disengagement and juvenile petitions for violent crimes, while RHR was unrelated to all measures of violent behavior. Interactive effects were also evident such that among men with lower but not higher levels of RHR, lower empathy predicted increased violent behavior, as indexed by juvenile arrests for violent offenses, peer-reported violent behavior at age 17, self-reported moral disengagement at age 17, and self-reported violent behavior at age 20.ConclusionsImplications for prevention and intervention are considered. Specifically, targeting empathic skills among individuals at risk for violent behavior because of specific psychophysiological profiles may lead to more impactful interventions