Publications made possible with iMotions

Abstract: The aim of this paper is to present PhD research that aims to enhance the User Experience by proposing a framework that combines the three core components of: dynamic interfaces; adaptive interfaces; and intelligent interfaces. Initial research into the field has identified a gap at the intersection of these types of interaction. A dynamic […]

Abstract: During interceptive motor tasks, experts demonstrate distinct visual search behavior (from novices) that is reflective of information extraction from optimal environmental cues, which subsequently aids anticipatory movements. While some forms of visual training have been employed in sport, over-speed video training is rarely applied to perceptual–cognitive sport contexts. The purpose of the present study […]

Abstract: Multimodal language analysis is an emerging research area in natural language processing that models language in a multimodal manner. It aims to understand language from the modalities of text, visual, and acoustic by modeling both intra-modal and cross-modal interactions. BERT (Bidirectional Encoder Representations from Transformers) provides strong contextual language representations after training on large-scale […]

Abstract: Floriculture value exceeds $5.8 billion in the United States. Environmental challenges, market trends, and diseases complicate breeding priorities. To inform breeders’ and geneticists’ research efforts, we set out to gather consumers’ preferences in the form of willingness to pay (WTP) for different rose attributes in a discrete choice experiment. The responses are modeled in […]

Abstract: A staggering report was recently released by the International Consortium of Investigative Journalists (ICIJ) indicating that 83,000 deaths and 1.7 million injuries were linked to medical device adverse events reported over the last decade (Díaz-Struck, 2018). Furthermore, a 2013 report by McKinsey & Company suggested that such adverse events and associated quality issues cost […]

Abstract: The growing sophistication of technologies and sociological advances are major causes for the dramatic change the automotive sector is currently undergoing. To address changes from a human-centered design perspective an improved understanding of the occupants’ emotional experience and behavior is required. Facial-Expression Analysis (FEA) is an emerging tool in support of such an approach, […]

Abstract: In this paper, we propose a novel multimodal fusion framework, named locally confined modality fusion network (LMFN), that contains a bidirectional multiconnected LSTM (BM-LSTM) to address the multimodal human affective computing problem. Instead of conducting fusion only on a holistic level, we propose a hierarchical fusion strategy that considers both local and global interactions […]

Abstract: This paper describes an exploratory usability study designed to investigate how college students locate information in a Learning Management System and to establish a set of guidelines for creating the best course layouts that can increase the student’s learning experience. Using observations, perception survey data, and a high-fidelity eye-tracker that recorded where participants’ eyes […]

Abstract: Can the magnitude of the calorie distance between food items explain the contradictory findings in previous literature regarding the impact of calorie labeling laws? Our theoretical model suggests that the relative calorie difference between alternatives in food menus is a missing link important for understanding the impact of calorie labeling information on calorie intake […]

Abstract: We propose a general strategy named ‘divide, conquer and combine’ for multimodal fusion. Instead of directly fusing features at holistic level, we conduct fusion hierarchically so that both local and global interactions are considered for a comprehensive interpretation of multimodal embeddings. In the ‘divide’ and ‘conquer’ stages, we conduct local fusion by exploring the […]

Abstract: Background In general, people are poor at detecting deception. Older adults are even worse than young adults at detecting deceit, which might make them uniquely vulnerable to certain types of financial fraud. One reason for poor deceit detection abilities is that lay theories of cues to deception are not valid. This study compared the […]

Abstract: This paper learns multi-modal embeddings from text, audio, and video views/modes of data in order to improve upon downstream sentiment classification. The experimental framework also allows investigation of the relative contributions of the individual views in the final multi-modal embedding. Individual features derived from the three views are combined into a multi-modal embedding using […]