14,600 research outputs found

    Multimodal Observation and Interpretation of Subjects Engaged in Problem Solving

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    In this paper we present the first results of a pilot experiment in the capture and interpretation of multimodal signals of human experts engaged in solving challenging chess problems. Our goal is to investigate the extent to which observations of eye-gaze, posture, emotion and other physiological signals can be used to model the cognitive state of subjects, and to explore the integration of multiple sensor modalities to improve the reliability of detection of human displays of awareness and emotion. We observed chess players engaged in problems of increasing difficulty while recording their behavior. Such recordings can be used to estimate a participant's awareness of the current situation and to predict ability to respond effectively to challenging situations. Results show that a multimodal approach is more accurate than a unimodal one. By combining body posture, visual attention and emotion, the multimodal approach can reach up to 93% of accuracy when determining player's chess expertise while unimodal approach reaches 86%. Finally this experiment validates the use of our equipment as a general and reproducible tool for the study of participants engaged in screen-based interaction and/or problem solving

    Eye Tracker Accuracy: Quantitative Evaluation of the Invisible Eye Center Location

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    Purpose. We present a new method to evaluate the accuracy of an eye tracker based eye localization system. Measuring the accuracy of an eye tracker's primary intention, the estimated point of gaze, is usually done with volunteers and a set of fixation points used as ground truth. However, verifying the accuracy of the location estimate of a volunteer's eye center in 3D space is not easily possible. This is because the eye center is an intangible point hidden by the iris. Methods. We evaluate the eye location accuracy by using an eye phantom instead of eyes of volunteers. For this, we developed a testing stage with a realistic artificial eye and a corresponding kinematic model, which we trained with {\mu}CT data. This enables us to precisely evaluate the eye location estimate of an eye tracker. Results. We show that the proposed testing stage with the corresponding kinematic model is suitable for such a validation. Further, we evaluate a particular eye tracker based navigation system and show that this system is able to successfully determine the eye center with sub-millimeter accuracy. Conclusions. We show the suitability of the evaluated eye tracker for eye interventions, using the proposed testing stage and the corresponding kinematic model. The results further enable specific enhancement of the navigation system to potentially get even better results

    The Usefulness of Multi-Sensor Affect Detection on User Experience: An Application of Biometric Measurement Systems on Online Purchasing

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    abstract: Traditional usability methods in Human-Computer Interaction (HCI) have been extensively used to understand the usability of products. Measurements of user experience (UX) in traditional HCI studies mostly rely on task performance and observable user interactions with the product or services, such as usability tests, contextual inquiry, and subjective self-report data, including questionnaires, interviews, and usability tests. However, these studies fail to directly reflect a user’s psychological involvement and further fail to explain the cognitive processing and the related emotional arousal. Thus, capturing how users think and feel when they are using a product remains a vital challenge of user experience evaluation studies. Conversely, recent research has revealed that sensor-based affect detection technologies, such as eye tracking, electroencephalography (EEG), galvanic skin response (GSR), and facial expression analysis, effectively capture affective states and physiological responses. These methods are efficient indicators of cognitive involvement and emotional arousal and constitute effective strategies for a comprehensive measurement of UX. The literature review shows that the impacts of sensor-based affect detection systems to the UX can be categorized in two groups: (1) confirmatory to validate the results obtained from the traditional usability methods in UX evaluations; and (2) complementary to enhance the findings or provide more precise and valid evidence. Both provided comprehensive findings to uncover the issues related to mental and physiological pathways to enhance the design of product and services. Therefore, this dissertation claims that it can be efficient to integrate sensor-based affect detection technologies to solve the current gaps or weaknesses of traditional usability methods. The dissertation revealed that the multi-sensor-based UX evaluation approach through biometrics tools and software corroborated user experience identified by traditional UX methods during an online purchasing task. The use these systems enhanced the findings and provided more precise and valid evidence to predict the consumer purchasing preferences. Thus, their impact was “complementary” on overall UX evaluation. The dissertation also provided information of the unique contributions of each tool and recommended some ways user experience researchers can combine both sensor-based and traditional UX approaches to explain consumer purchasing preferences.Dissertation/ThesisDoctoral Dissertation Human Systems Engineering 201

    A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms

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    In this paper a review is presented of the research on eye gaze estimation techniques and applications, that has progressed in diverse ways over the past two decades. Several generic eye gaze use-cases are identified: desktop, TV, head-mounted, automotive and handheld devices. Analysis of the literature leads to the identification of several platform specific factors that influence gaze tracking accuracy. A key outcome from this review is the realization of a need to develop standardized methodologies for performance evaluation of gaze tracking systems and achieve consistency in their specification and comparative evaluation. To address this need, the concept of a methodological framework for practical evaluation of different gaze tracking systems is proposed.Comment: 25 pages, 13 figures, Accepted for publication in IEEE Access in July 201

    An Enterprise 2.0 project management approach to facilitate participation, transparency, and communication

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    The use of current interactive and collaborative Web 2.0 concepts and technologies has great potential for flexible, loosely-coupled integration and ad-hoc information exchange within and between organizations. However, stakeholders’ readiness, willingness and ability to participate need to be continuously factored in. The successful implementation of common strategies, systems and processes in the course of Enterprise 2.0 projects is crucial. To increase the probability of success and to enhance the intensity of cooperation and trust in such projects, the constructs of transparency, communication and participation need to be addressed through an integrated project methodology. To bridge the gap between existing scientific models and requirements for Enterprise 2.0 projects, this paper proposes and describes a project methodology to support the main objectives for Enterprise 2.0 implementations. Selected results from two pilot projects within Austrian companies are presented and matched with critical success factors, which are derived from the literature. These provide elaborative insights into key characteristics of certain Enterprise 2.0 tools and project management for Enterprise 2.0 projects

    Evaluating Medical Devices Remotely: Current Methods and Potential Innovations

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    Objective: We present examples of laboratory and remote studies, with a focus on studies appropriate for medical device design and evaluation. From this review and description of extant options for remote testing, we provide methods and tools to achieve research goals remotely. Background: The FDA mandates human factors evaluation of medical devices. Studies show similarities and differences in results collected in laboratories compared to data collected remotely in non-laboratory settings. Remote studies show promise, though many of these are behavioral studies related to cognitive or experimental psychology. Remote usability studies are rare but increasing, as technologies allow for synchronous and asynchronous data collection. Method: We reviewed methods of remote evaluation of medical devices, from testing labels and instruction to usability testing and simulated use. Each method was coded for the attributes (e.g., supported media) that need consideration in usability studies. Results: We present examples of how published usability studies of medical devices could be moved to remote data collection. We also present novel systems for creating such tests, such as the use of 3D printed or virtual prototypes. Finally, we advise on targeted participant recruitment. Conclusion: Remote testing will bring opportunities and challenges to the field of medical device testing. Current methods are adequate for most purposes, excepting the validation of Class III devices. Application: The tools we provide enable the remote evaluation of medical devices. Evaluations have specific research goals, and our framework of attributes helps to select or combine tools for valid testing of medical devices

    About the nature of Kansei information

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    Kansei studies refer to the more and more holistic consideration of the cognitive and affective processes which occur during user experience. In addition, few studies deal with the experience of the designers during the design process, and its influence on the final design outputs. Historically kansei engineering has been firstly focused on the semantic differential approach. Afterwards emotions were integrated into kansei approaches. The semantic differential approach enabled to evaluate products and then to generate automatically design solutions with semantic input data. Thereafter, evaluations have been completed by physiological measurements in order to reduce the subjectivity involved in those evaluations and also to capture some unconscious reactions. This implementation is still in process. Today kansei studies have been much enriched from the three disciplines of design science, psychology and artificial intelligence. The cross influence between these disciplines brought new dimensions into kansei approaches (multisensory design information, personality, values, and culture, new formalisms and algorithms) which lead progressively towards the consideration of a whole enriched kansei experience. We propose in this paper a description of the nature of kansei information. Then we present some major orientations for kansei evaluation. Finally we propose an overall table gathering information about kansei dimensions and formats.AN
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