Virtual reality (VR) technologies have shown promising potential in the early diagnosis of dementia by enabling accessible and regular assessment. However, previous VR studies were restricted to the analysis of behavioral responses, so information about degenerated brain dynamics could not be directly acquired. To address this issue, we provide a cognitive impairment (CI) screening tool based on a wearable EEG device integrated into a VR platform. Subjects were asked to use a hardware setup consisting of a frontal six-channel EEG device mounted on a VR device and to perform four cognitive tasks in VR. Behavioral response profiles and EEG features were extracted during the tasks, and classifiers were trained on extracted features to differentiate subjects with CI from healthy controls (HCs). Notably, the performance of the patient classification consistently improved when EEG characteristics measured during cognitive tasks were additionally included in feature attributes than when only the task scores or resting-state EEG features were used, suggesting that our protocol provides discriminative information for screening. These results propose that the integration of EEG devices into a VR framework could emerge as a powerful and synergistic strategy for constructing an easily accessible EEG-based CI screening tool.