Utilizing Dry Electrode Electroencephalography and AI Robotics for Cognitive Stress Monitoring in Video Gaming  
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color, is the stacked count of publications specifically focused on EEG and Video Gaming [10; 11]. This visualization highlights the growth and research interest in both fields, with a particular emphasis on the intersection of EEG technology and video gaming studies.  
Social robots, being developed and conceived for different applications [12], have been used in different studies related to human cognition and mental activity. Stress management interventions [13], social anxiety interventions [14], and social cognition studies [15] are examples of such applications. To be used in such tasks, a social robot can benefit from capabilities in sound and image acquisition and processing, sound emission and expression display, Additionally, the ability to make conversations is important in contexts of assistive social robotics for realistic and engaging interactions with humans, and the usage of generative artificial intelligence tools for this task can be of high benefit. In this context, Furhat has been used in conjunction with language models in studies related to different areas of human-robot interaction [16; 17].  
At the intersection of the aforementioned technologies, this paper presents a novel integration of the Dry Sensor Interface-24 (DSI-24) [18] EEG headset with a ChatGPT-enabled Furhat robot, aimed at monitoring and analyzing cognitive stress in video gaming environments. The main components of the system have been combined as follows:  
* The DSI-24 is a state-of-the-art wireless EEG device, highly efficient in capturing brainwave activity in real-time, making it an ideal tool for dynamic and interactive settings such as video gaming.
* The Furhat [19] social robot (available: [[https://furhatrobotics.com/furhat-robot/](https://furhatrobotics.com/furhat-robot/)]([https://furhatrobotics.com/furhat-robot/](https://furhatrobotics.com/furhat-robot/)), accessed on 29 May 2024) is one of the emerging platforms that can be employed in human-robot interaction with a variety of applications.
* ChatGPT (available: [[https://openai.com/chatgpt/](https://openai.com/chatgpt/)]([https://openai.com/chatgpt/](https://openai.com/chatgpt/)), accessed on 29 May 2024) has been seen as a flexible tool for text generation, which can be adapted to different context through user prompts. While it is mainly accessed through a web browser, it can be accessed through an API embedded in a program serving a specific application.  
While these components have already existed and have been used in different research areas, their combination in the context of stress monitoring and video gaming is a novel usage that has been tailored in this work to make use of their capabilities efficiently. The primary objective of this work is to identify and analyze indicators of cognitive stress among video game players. By analyzing EEG data, we aim to gain insights into the mental states of players during gaming sessions, particularly focusing on stress levels and cognitive load. The integration with a ChatGPT-powered Furhat robot is a crucial aspect  
Figure 1: Number of Scopus-indexed conference and journal papers on ’Video Gaming’ compared to those specifically on ’EEG and Video Gaming’ over the academic years 2010–2023.  
of our study, as this AI-driven interface assists in both guiding players through the data collection process and providing timely interventions, such as suggesting breaks, when high stress levels are detected.  
This article is organized as follows: Section 2, describes the system level design, detailing the integration of the Dry Sensor Interface-24 (DSI-24) EEG headset with the ChatGPT-enabled Furhat robot. Section 3, presents the findings of the conducted experiments and their implications. Section 4, outlines the limitations of the proposed system and potential avenues for further research and exploration. Finally, a conclusion in given in Section 5.