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Titlebook: Information Systems and Neuroscience; NeuroIS Retreat 2021 Fred D. Davis,René Riedl,Gernot Müller-Putz Conference proceedings 2021 The Edit

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31#
發(fā)表于 2025-3-26 23:22:21 | 只看該作者
Exploring the Recognition of Facial Activities Through Around-The-Ear Electrode Arrays (cEEGrids),p adaptive IS that foster individual and organizational productivity, growth, and well-being. Collecting such data often requires multiple recording devices, which leads to inflated study cost and decreased external validity due to greater intrusion in natural behavior. To overcome this problem, we
32#
發(fā)表于 2025-3-27 04:38:34 | 只看該作者
33#
發(fā)表于 2025-3-27 07:22:21 | 只看該作者
34#
發(fā)表于 2025-3-27 09:49:25 | 只看該作者
,“Overloading” Cognitive (Work)Load: What Are We Really Measuring?,een 2012 and 2020 which included measurement of cognitive load or related constructs. This paper reviews terminology used to refer to cognitive load, mental workload and its variations, as well as their operationalizations and measurements. All 27 papers employed physiological NeuroIS measures, whil
35#
發(fā)表于 2025-3-27 15:41:31 | 只看該作者
36#
發(fā)表于 2025-3-27 21:12:32 | 只看該作者
Predicting In-Field Flow Experiences Over Two Weeks from ECG Data: A Case Study,o understand and support flow during IS use. In this direction, a limitation has been the focus on cross-subject models built on data collected in controlled laboratory settings. We investigate the potential of predicting flow in the field through personalized models by collecting report and ECG dat
37#
發(fā)表于 2025-3-28 00:39:52 | 只看該作者
38#
發(fā)表于 2025-3-28 05:41:14 | 只看該作者
EyeTC: Attentive Terms and Conditions of Internet-Based Services with Webcam-Based Eye Tracking,ng T&C most of the time and accept them tacitly without reading, while they may include critical information. This study targets solving this problem by designing an innovative NeuroIS application called EyeTC. EyeTC uses webcam-based eye tracking technology to track users’ eye movement data in real
39#
發(fā)表于 2025-3-28 07:17:47 | 只看該作者
Detecting Flow Experiences in the Field Using Video-Based Head and Face Activity Recognition: A Pile to a lack of automatic and unobtrusive detection methods, NeuroIS scholars face the opportunity to devise measurement approaches for flow experience during IS use and, moreover, flow supporting, adaptive NeuroIS. This work presents the first results from a controlled experience sampling field stud
40#
發(fā)表于 2025-3-28 10:50:44 | 只看該作者
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