Abstract: Mitigating human errors is a priority in the design of complex systems, especially through the use of body area networks. This paper describes early developments of a dynamic data driven platform to predict operator error and trigger appropriate intervention before the error happens. Using a two-stage process, data was collected using several sensors (e.g. […]

Abstract: Research on decision making in engineering design has focused primarily on how to make decisions using normative models given certain information. However, there exists a research gap on how diverse information stimuli are combined by designers in decision making. In this paper, we address the following question: how do designers weigh different information stimuli to […]

Abstract: This short paper presents initial results from a project, in which we investigated differences in how users view relevant and irrelevant Web pages on their visits and revisits. The users’ viewing of Web pages was characterized by eye-tracking measures, with a particular attention paid to changes in pupil size. The data was collected in […]

Abstract: Consumers’ product purchase decisions typically involve comparing competing products’ visual features and functional attributes. Companies strive for “product differentiation” [1-5], which makes consumers’ product comparisons fruitful but also sometimes challenging. Psychologists that study decision-making have created models of choice such as the cancellation-and-focus (C&F) model. C & Fexplains and predicts how people decide between choice […]

Abstract: We have developed a neuromodulation approach that targets peripheral nerves and utilizes their afferents as signaling conduits to influence brain function. We investigated the effects of this transdermal electrical neurosignaling (TEN) approach on physiological responses to acute stress induction. TEN was targeted to the ophthalmic and maxillary divisions of the right trigeminal nerve and […]

Abstract: Mitigating human errors is a priority in the design of complex systems, especially through the use of body area networks. This paper describes early developments of a dynamic data driven platform to predict operator error and trigger appropriate intervention before the error happens. Using a two-stage process, data was collected using several sensors (e.g., […]

Abstract: We present initial results from a project, in which we examined feasibility of inferring web page relevance from eye-tracking data. We conduced a controlled, lab-based Web search experiment, in which participants conducted assigned information search tasks on Wikipedia. We performed analyses of variance as well as employed classification algorithms in order to predict user […]

Abstract: Affect detection is a key component in developing intelligent educational interfaces that are capable of responding to the affective needs of students. In this paper, computer vision and machine learning techniques were used to detect students’ affect as they used an educational game designed to teach fundamental principles of Newtonian physics. Data were collected […]

Abstract: Investigating how visuals affect test takers’ performance on video-based L2 listening tests has been the focus of many recent studies. While most existing research has been based on test scores and self-reported verbal data, few studies have examined test takers’ viewing behavior (Ockey, 2007; Wagner, 2007, 2010a). To address this gap, in the present […]

Present study on cognitive workload in driving focuses on reduction of workload for better driving performance. In this paper, we talk about the cognitive load in drivers of autonomous cars and their performance under multiple cognitive loads. Our previous studies have indicated that low to no workload is likely to induce drowsiness in drivers of […]