| Full text | |
| Author(s): |
Consoli, Rodrigo A.
;
Colli, Eduardo
;
Soares Jr, Raimundo da Silva Soares
;
Sato, Joao R.
;
Marson, Guilherme A.
Total Authors: 5
|
| Document type: | Journal article |
| Source: | JOVE-JOURNAL OF VISUALIZED EXPERIMENTS; v. N/A, n. 212, p. 26-pg., 2024-10-01. |
| Abstract | |
We present a method for real-time recording of human interaction with threedimensional (3D) virtual objects. The approach consists of associating rotation data of the manipulated object with behavioral measures, such as eye tracking, to make better inferences about the underlying cognitive processes. The task consists of displaying two identical models of the same 3D object (a molecule), presented on a computer screen: a rotating, interactive object (iObj) and a static, target object (tObj). Participants must rotate iObj using the mouse until they consider its orientation to be identical to that of tObj. The computertracks all interaction data in real time. The participant's gaze data are also recorded using an eye tracker. The measurement frequency is 10 Hz on the computer and 60 Hz on the eye tracker. The orientation data of iObj with respect to tObj are recorded in rotation quaternions. The gaze data are synchronized to the orientation of iObj and referenced using this same system. This method enables us to obtain the following visualizations of the human interaction process with iObj and tObj: (1) angular disparity synchronized with other time-dependent data; (2) 3D rotation trajectory inside what we decided to call a "ball of rotations"; (3) 3D fixation heatmap. All steps of the protocol have used free software, such as GNU Octave and Jmol, and all scripts are available as supplementary material. With this approach, we can conduct detailed quantitative studies of the task-solving process involving mental or physical rotations, rather than only the outcome reached. It is possible to measure precisely how important each part of the 3D models is for the participant in solving tasks, and thus relate the models to relevant variables such as the characteristics of the objects, cognitive abilities of the individuals, and the characteristics of human-machine interface. (AU) | |
| FAPESP's process: | 23/02538-0 - Time series, wavelets, high dimensional data and applications |
| Grantee: | Aluísio de Souza Pinheiro |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 18/21934-5 - Network statistics: theory, methods, and applications |
| Grantee: | André Fujita |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 18/04654-9 - Time series, wavelets and high dimensional data |
| Grantee: | Pedro Alberto Morettin |
| Support Opportunities: | Research Projects - Thematic Grants |