TY - GEN A1 - Hernandez, Netzahualcoyotl A1 - Demiray, Burcu A1 - Arnrich, Bert A1 - Favela, Jesus T1 - An Exploratory Study to Detect Temporal Orientation Using Bluetooth's sensor T2 - PervasiveHealth'19: Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare N2 - Mobile sensing technology allows us to investigate human behaviour on a daily basis. In the study, we examined temporal orientation, which refers to the capacity of thinking or talking about personal events in the past and future. We utilise the mksense platform that allows us to use the experience-sampling method. Individual's thoughts and their relationship with smartphone's Bluetooth data is analysed to understand in which contexts people are influenced by social environments, such as the people they spend the most time with. As an exploratory study, we analyse social condition influence through a collection of Bluetooth data and survey information from participant's smartphones. Preliminary results show that people are likely to focus on past events when interacting with close-related people, and focus on future planning when interacting with strangers. Similarly, people experience present temporal orientation when accompanied by known people. We believe that these findings are linked to emotions since, in its most basic state, emotion is a state of physiological arousal combined with an appropriated cognition. In this contribution, we envision a smartphone application for automatically inferring human emotions based on user's temporal orientation by using Bluetooth sensors, we briefly elaborate on the influential factor of temporal orientation episodes and conclude with a discussion and lessons learned. KW - Mobile sensing KW - Temporal orientation KW - Social environment KW - Human behaviour KW - Bluetooth Y1 - 2019 SN - 978-1-4503-6126-2 U6 - https://doi.org/10.1145/3329189.3329223 SN - 2153-1633 SP - 292 EP - 297 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Schwetlick, Lisa A1 - Rothkegel, Lars Oliver Martin A1 - Trukenbrod, Hans Arne A1 - Engbert, Ralf T1 - Modeling the effects of perisaccadic attention on gaze statistics during scene viewing JF - Communications biology N2 - Lisa Schwetlick et al. present a computational model linking visual scan path generation in scene viewing to physiological and experimental work on perisaccadic covert attention, the act of attending to an object visually without obviously moving the eyes toward it. They find that integrating covert attention into predictive models of visual scan paths greatly improves the model's agreement with experimental data.
How we perceive a visual scene depends critically on the selection of gaze positions. For this selection process, visual attention is known to play a key role in two ways. First, image-features attract visual attention, a fact that is captured well by time-independent fixation models. Second, millisecond-level attentional dynamics around the time of saccade drives our gaze from one position to the next. These two related research areas on attention are typically perceived as separate, both theoretically and experimentally. Here we link the two research areas by demonstrating that perisaccadic attentional dynamics improve predictions on scan path statistics. In a mathematical model, we integrated perisaccadic covert attention with dynamic scan path generation. Our model reproduces saccade amplitude distributions, angular statistics, intersaccadic turning angles, and their impact on fixation durations as well as inter-individual differences using Bayesian inference. Therefore, our result lend support to the relevance of perisaccadic attention to gaze statistics. KW - Computational models KW - Human behaviour KW - Visual system Y1 - 2020 U6 - https://doi.org/10.1038/s42003-020-01429-8 SN - 2399-3642 VL - 3 IS - 1 PB - Springer Nature CY - London ER -