Cepeda Catia, Dias Maria Camila, Rindlisbacher Dina, Gamboa Hugo, Cheetham Marcus
Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland.
LIBPhys (Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal.
Heliyon. 2021 Jan 22;7(1):e05873. doi: 10.1016/j.heliyon.2020.e05873. eCollection 2021 Jan.
Pointer-tracking methods can capture a real-time trace at high spatio-temporal resolution of users' pointer interactions with a graphical user interface. This trace is potentially valuable for research on human-computer interaction (HCI) and for investigating perceptual, cognitive and affective processes during HCI. However, little research has reported spatio-temporal pointer features for the purpose of tracking pointer movements in on-line surveys. In two studies, we identified a set of pointer features and movement patterns and showed that these can be easily distinguished. In a third study, we explored the feasibility of using patterns of interactive pointer movements, or micro-behaviours, to detect response uncertainty. Using logistic regression and k-fold cross-validation in model training and testing, the uncertainty model achieved an estimated performance accuracy of 81%. These findings suggest that micro-behaviours provide a promising approach toward developing a better understanding of the relationship between the dynamics of pointer movements and underlying perceptual, cognitive and affective psychological mechanisms.
指针跟踪方法能够以高时空分辨率捕捉用户与图形用户界面进行指针交互的实时轨迹。这条轨迹对于人机交互（HCI）研究以及调查人机交互过程中的感知、认知和情感过程具有潜在价值。然而，很少有研究报道用于在线调查中跟踪指针移动的时空指针特征。在两项研究中，我们识别出了一组指针特征和移动模式，并表明这些特征和模式很容易区分。在第三项研究中，我们探讨了使用交互式指针移动模式或微观行为来检测响应不确定性的可行性。在模型训练和测试中使用逻辑回归和k折交叉验证，不确定性模型实现了81%的估计性能准确率。这些发现表明，微观行为为更好地理解指针移动动态与潜在的感知、认知和情感心理机制之间的关系提供了一种很有前景的方法。
