Democratizing Psychophysiological Research: Leveraging Open Resources for Experimental Settings and Data Analysis of Flow, Engagement, and Performance.

EasyChair Preprint 14193

Abstract

Contemporary research faces challenges due to economic constraints and a lack of specialized software. However, advancements such as affordable wearable sensors and collaborative platforms like GitHub are revolutionizing this landscape.
This work proposes the development of an experimental setup that integrates game stimuli presentation and synchronized recording of facial movements and cardiac data, facilitating resource sharing and collaboration. The objective of this framework is to elicit and detect states of flow and engagement along with associated physiological activations. Using different difficulty levels of a Tetris-style game as stimuli, the framework synchronizes players’ activity with Interbeat interval (IBI) data from the Polar H10 cardiac chest band and webcam videos. Key to the approach is precise data synchronization using timestamps and established libraries like LabStreamingLayer (LSL). Three Python scripts manage Tetris presentation, Polar H10 Bluetooth connection for cardiac data collection, and video frame tagging for facial expression analysis. These scripts adhere to FAIR principles and provide a practical implementation for studying psychophysiological responses. By leveraging open resources, this framework addresses economic and software limitations and allows for adaptation to various research questions or theoretical constructs.

Keyphrases: Affective Computing, ECG, Emotions, Performance, Physiological reactions, facial expressions, flow, open source, video game

@booklet{EasyChair:14193,
  author    = {Elena Sajno and Samantha Chen and Federico Dagostin and Stefano De Gaspari and Chiara Pupillo and Giuseppe Riva},
  title     = {Democratizing Psychophysiological Research: Leveraging Open Resources for Experimental Settings and Data Analysis of Flow, Engagement, and Performance.},
  howpublished = {EasyChair Preprint 14193},
  year      = {EasyChair, 2024}}