Jessica Beltrán
ABSTRACT
The analysis of eye fixations during a Visual Paired Comparison Task is useful to measure novelty preference, which has been correlated with mental health status. The experimentation with the Visual Paired Comparison Task has been mainly conducted with commercial high-performance eye trackers and different experimental setup constraints. Recent research has shown that a web camera-based eye tracking can gather useful data with the Visual Paired Comparison Task. The ubiquitous web camera gives different possibilities for pervasive mental health assessment. We conducted a preliminary study where participants are not only observers in the Visual Paired Comparison Task, but they can interact with the system by moving over displayed images at their own pace. We collected data from 23 participants using a web camera based eye tracker. We discuss the novelty preference from participants that are only observers and with participants that can freely advance through the images.
- Jessica Beltrán, Mireya S García-Vázquez, Jenny Benois-Pineau, Luis Miguel Gutierrez-Robledo, and Jean-François Dartigues. 2018. Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review. Computational and Mathematical Methods in Medicine 2018 (2018).Google Scholar
- Nicholas T Bott, Alex Lange, Dorene Rentz, Elizabeth Buffalo, Paul Clopton, and Stuart Zola. 2017. Web Camera Based Eye Tracking to Assess Visual Memory on a Visual Paired Comparison Task. Frontiers in neuroscience 11 (2017), 370.Google Scholar
- Luis A Maldonado Cano, Jessica Beltrán, René Navarro, Mireya S García-Vázquez, and Luis A Castro. 2017. Towards early dementia detection by oculomotor performance analysis on leisure web content. In Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. ACM, 800--804. Google ScholarDigital Library
- Sarah A Chau, Nathan Herrmann, Moshe Eizenman, Jonathan Chung, and Krista L Lanctôt. 2015. Exploring visual selective attention towards novel stimuli in Alzheimer's disease patients. Dementia and geriatric cognitive disorders extra 5, 3 (2015), 492--502.Google Scholar
- Sarah A Chau, Nathan Herrmann, Chelsea Sherman, Jonathan Chung, Moshe Eizenman, Alex Kiss, and Krista L Lanctôt. 2017. Visual Selective Attention Toward Novel Stimuli Predicts Cognitive Decline in Alzheimer's Disease Patients. Journal of Alzheimer's Disease 55, 4 (2017), 1339--1349.Google ScholarCross Ref
- Trevor J Crawford. 2015. The disengagement of visual attention in Alzheimer's disease: a longitudinal eye-tracking study. Frontiers in aging neuroscience 7 (2015), 118.Google Scholar
- Gerardo Fernández, Facundo Manes, Luis E Politi, David Orozco, Marcela Schumacher, Liliana Castro, Osvaldo Agamennoni, and Nora P Rotstein. 2016. Patients with Mild Alzheimer's Disease Fail When Using Their Working Memory: Evidence from the Eye Tracking Technique. Journal of Alzheimer's Disease 50, 3 (2016), 827--838.Google ScholarCross Ref
- Alexandra Papoutsaki, Patsorn Sangkloy, James Laskey, Nediyana Daskalova, Jeff Huang, and James Hays. 2016. WebGazer: Scalable Webcam Eye Tracking Using User Interactions. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI). AAAI, 3839--3845. Google ScholarDigital Library
- Yani Shi, Qing Zeng, Fiona Fui-Hoon Nah, Chuan-Hoo Tan, Choon Ling Sia, Keng Siau, and Jiaqi Yan. 2017. Effect of Timing and Source of Online Product Recommendations: An Eye-Tracking Study. In International Conference on HCI in Business, Government, and Organizations. Springer, 95--104.Google Scholar
- Katerina Tzafilkou and Nicolaos Protogeros. 2017. Diagnosing user perception and acceptance using eye tracking in web-based end-user development. Computers in Human Behavior 72 (2017), 23--37. Google ScholarDigital Library
- Natalia I Vargas-Cuentas, Avid Roman-Gonzalez, Robert H Gilman, Franklin Barrientos, James Ting, Daniela Hidalgo, Kelly Jensen, and Mirko Zimic. 2017. Developing an eye-tracking algorithm as a potential tool for early diagnosis of autism spectrum disorder in children. PloS one 12, 11 (2017), e0188826.Google ScholarCross Ref
- Stuart M Zola, CM Manzanares, P Clopton, JJ Lah, and AI Levey. 2013. A behavioral task predicts conversion to mild cognitive impairment and Alzheimer's disease. American Journal of Alzheimer's Disease & Other Dementias® 28, 2 (2013), 179--184.Google Scholar
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