Extreme attention assessment of cluster drone operators
Leiming Jin, Xiaochuan Zhao, Huapeng Liu, Ying Liu, Yunduo Feng, Tiange Hong · 2024
The extreme attention state is one of the cognitive states and it is extremely important for cluster operators due to the diversity and complexity of tasks. However, existing research tends to be more theoretical and there is relatively little research on extreme attention states. Therefore, we combine theoretical research with practical cluster drone control task to design our experimental paradigm. We used machine learning method to build classifiers and all of these classifiers achieved good results, which validates the rationality of our method. Finally, we choose the support vector machine (SVM) as our classifier due to the excellent result.