Physiological signals have emerged as a promising avenue for understanding human behavior and cognition, particularly in real-world settings (Ananthan et al., 2024). Recent advancements in wearable sensor technology have enabled continuous monitoring of various physiological markers, such as electrodermal activity and heart rate, providing insights into individuals' emotional and cognitive states. (Gibilisco et al., 2018)
One of the key applications of these psychophysiological advancements lies in understanding student engagement and learning dynamics. Researchers have found that physiological signals can serve as effective indicators of academic stress, anxiety, and engagement, complementing traditional self-report and observational measures. (Jiménez-Mijangos et al., 2022) (Ananthan et al., 2024) By monitoring students' physiological responses across different courses, researchers have identified unique patterns that enhance our understanding of intra-individual variations in cognitive and emotional responses to various learning environments. (Ananthan et al., 2024)
These applications extend beyond the classroom, with the potential to inform clinical and social neuroscience research. Clinicians and researchers have explored the use of feedback techniques, such as neurofeedback, to allow participants to self-regulate their physiological and mental states, leading to promising results in the treatment of various psychiatric disorders (Orndorff-Plunkett et al., 2017).
Despite these advancements, there are still significant challenges in bringing physiological detection systems into real-world settings, such as the classroom. The use of non-invasive, wearable sensors is critical to minimize the intrinsic stress caused by instrumentation, ensuring that the physiological responses captured reflect the natural state of the individuals.
