xDelia final report: emotion-centred financial decision making and learning

xDelia is a 3-year pan-European project building on the knowledge, skills, and competences of seven partner organisations from a variety of research disciplines and from business. The principal objective of xDelia is to develop technology-enhanced learning approaches that help improve the financial decision making of investors who trade frequently using an electronic trading platform. We focus on emotions, and how they affect maladaptive decision biases and trading performance. Our earlier field work with traders has shown that the development of emotion regulation skills is a key facet of trader expertise. For that reason we consider expert traders our benchmark for adaptive behaviour rather than normative rationality. Our goal is to provide investors with the tools and techniques to develop greater self-awareness of internal states, increase their ability to reflect critically on emotion-informed choices, develop emotion management skills, and support the transfer of these skills to the real-world practice setting of financial trading. This report provides a comprehensive overview of what xDelia is about and what we have achieved over the life of the project. In the sections that follow, we explain the decision problems investors are faced with in a fast paced environment and the limitations of traditional approaches to reduce cognitive errors; introduce an alternative, technology-enhanced learning approach of diagnosis and feedback, skill development, and transfer; describe the learning intervention comprising twelve autonomous learning elements that we have developed; and present evidence from thirty-five studies we have conducted on learning effects and stakeholder acceptance

Information and communication technology solutions for outdoor navigation in dementia

INTRODUCTION: Information and communication technology (ICT) is potentially mature enough to empower outdoor and social activities in dementia. However, actual ICT-based devices have limited functionality and impact, mainly limited to safety. What is an ideal operational framework to enhance this field to support outdoor and social activities? METHODS: Review of literature and cross-disciplinary expert discussion. RESULTS: A situation-aware ICT requires a flexible fine-tuning by stakeholders of system usability and complexity of function, and of user safety and autonomy. It should operate by artificial intelligence/machine learning and should reflect harmonized stakeholder values, social context, and user residual cognitive functions. ICT services should be proposed at the prodromal stage of dementia and should be carefully validated within the life space of users in terms of quality of life, social activities, and costs. DISCUSSION: The operational framework has the potential to produce ICT and services with high clinical impact but requires substantial investment

A Framework for Psychophysiological Classification within a Cultural Heritage Context Using Interest

This article presents a psychophysiological construct of interest as a knowledge emotion and illustrates the importance of interest detection in a cultural heritage context. The objective of this work is to measure and classify psychophysiological reactivity in response to cultural heritage material presented as visual and audio. We present a data processing and classification framework for the classification of interest. Two studies are reported, adopting a subject-dependent approach to classify psychophysiological signals using mobile physiological sensors and the support vector machine learning algorithm. The results show that it is possible to reliably infer a state of interest from cultural heritage material using psychophysiological feature data and a machine learning approach, informing future work for the development of a real-time physiological computing system for use within an adaptive cultural heritage experience designed to adapt the provision of information to sustain the interest of the visitor

Neurophysiological Assessment of Affective Experience

In the field of Affective Computing the affective experience (AX) of the user during the interaction with computers is of great interest. The automatic recognition of the affective state, or emotion, of the user is one of the big challenges. In this proposal I focus on the affect recognition via physiological and neurophysiological signals. Long‐standing evidence from psychophysiological research and more recently from research in affective neuroscience suggests that both, body and brain physiology, are able to indicate the current affective state of a subject. However, regarding the classification of AX several questions are still unanswered. The principal possibility of AX classification was repeatedly shown, but its generalisation over different task contexts, elicitating stimuli modalities, subjects or time is seldom addressed. In this proposal I will discuss a possible agenda for the further exploration of physiological and neurophysiological correlates of AX over different elicitation modalities and task contexts

A First Step toward the Understanding of Implicit Learning of Hazard Anticipation in Inexperienced Road Users Through a Moped-Riding Simulator

Hazard perception is considered one of the most important abilities in road safety. Several efforts have been devoted to investigating how it improves with experience and can be trained. Recently, research has focused on the implicit aspects of hazard detection, reaction, and anticipation. In the present study, we attempted to understand how the ability to anticipate hazards develops during training with a moped-riding simulator: the Honda Riding Trainer (HRT). Several studies have already validated the HRT as a tool to enhance adolescents\u2019 hazard perception and riding abilities. In the present study, as an index of hazard anticipation, we used skin conductance response (SCR), which has been demonstrated to be linked to affective/implicit appraisal of risk. We administered to a group of inexperienced road users five road courses two times a week apart. In each course, participants had to deal with eight hazard scenes (except one course that included only seven hazard scenes). Participants had to ride along the HRT courses, facing the potentially hazardous situations, following traffic rules, and trying to avoid accidents. During the task, we measured SCR and monitored driving performance. The main results show that learning to ride the simulator leads to both a reduction in the number of accidents and anticipation of the somatic response related to hazard detection, as proven by the reduction of SCR onset recorded in the second session. The finding that the SCR signaling the impending hazard appears earlier when the already encountered hazard situations are faced anew suggests that training with the simulator acts on the somatic activation associated with the experience of risky situations, improving its effectiveness in detecting hazards in advance so as to avoid accidents. This represents the starting point for future investigations into the process of generalization of learning acquired in new virtual situations and in real-road situations

Brain-wave measures of workload in advanced cockpits: The transition of technology from laboratory to cockpit simulator, phase 2

The present Phase 2 small business innovation research study was designed to address issues related to scalp-recorded event-related potential (ERP) indices of mental workload and to transition this technology from the laboratory to cockpit simulator environments for use as a systems engineering tool. The project involved five main tasks: (1) Two laboratory studies confirmed the generality of the ERP indices of workload obtained in the Phase 1 study and revealed two additional ERP components related to workload. (2) A task analysis' of flight scenarios and pilot tasks in the Advanced Concepts Flight Simulator (ACFS) defined cockpit events (i.e., displays, messages, alarms) that would be expected to elicit ERPs related to workload. (3) Software was developed to support ERP data analysis. An existing ARD-proprietary package of ERP data analysis routines was upgraded, new graphics routines were developed to enhance interactive data analysis, and routines were developed to compare alternative single-trial analysis techniques using simulated ERP data. (4) Working in conjunction with NASA Langley research scientists and simulator engineers, preparations were made for an ACFS validation study of ERP measures of workload. (5) A design specification was developed for a general purpose, computerized, workload assessment system that can function in simulators such as the ACFS

Emotions and Emotion Regulation in Economic Decision Making

By employing the methodology of experimental economics, the thesis examines the influence of emotions on decision making in electronic auction markets. Subjects\u27 emotional processes are measured by psychophysiological indicators, helping to decipher the coherence of information, emotion (regulation) and decision making. Four chapters build the main body of the thesis and all are constructed similarly: introduction, design, method, results, limitations, theoretical and managerial implications

IS Cognitive Load: An Examination of Measurement Convergence

Despite the growth and interest in information processing research, understanding the supporting role of information systems (IS) has been limited. While cognitive processing of information has been examined in learning environments with traditional learning tasks, the investigation of cognitive load within complex simulated IS learning environments has received less attention. Traditional measurement allows for a broad user evaluation of the ISs and actual usage from a holistic perspective; however, detailed synchronous evaluation of cognitive load during the usage of the IS may allow for more accurate assessment of how system features influence cognitive load and subsequent performance outcomes. Therefore, this research attempts to integrate traditional subjective and physiological measurements to examine cognitive load within a dynamic simulated IS learning environment. This research study focuses on how subjective and objective physiological (galvanic skin response (GSR), heart rate variability (HRV), and electroencephalography (EEG) measures of cognitive load compare in simulated IS training environments

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 153)

This bibliography lists 175 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1976