NPFC-Test 23A: A dataset for assessing neuronal, physiological, and facial coding attributes in a human-computer interaction learning scenario

This dataset was collected through the NPFC-Test experiment, focused on capturing neural, physiological, and facial coding modalities for assessing concentration and motivation in students. The experiment involved the use of advanced biometric sensors to monitor brainwaves, biomarkers, facial gestures, and self-reported engagement levels. Using biometric devices (Muse 2, Empatica EmbracePlus, Azure Kinect), data were obtained during various tasks, including audiovisual content interactions, comprehension exercises, and self-evaluations. This database is pioneering in providing publicly accessible data that correlates facial gestures, physiological signals, and self-reported metrics during educational tasks. It serves as a valuable resource for research at the intersection of neuroeducation and student engagement, supporting interdisciplinary collaborations to further understand cognitive and emotional responses in learning environments. The database contains the following variables collected during the NPFC-Test experiment: - Timestamp variable records the unique date and time identifier in the format "yyyy/mm/dd HH:MM". - Subject_ID is a unique text identifier for each user, formatted as "IFE-EC-NPFC-T003-NN", where NN can range from 00 to 49. - Test_Time shows the elapsed time in the test in the format "HH:MM". - Task_Num identifies the task with specific values, such as 1.1 for demographic information or 8.1 for final meditation. - Task_Time indicates the time spent on each task. - Task_Type classifies the task as 0 (Self-evaluation), 1 (Focus), or 2 (Emotions). - Frame and Task_Frame variables are used to identify each analyzed video frame, every 30 frames. - Self-report responses are found in Selfreport_valence, Selfreport_arousal, and Selfreport_focus, with numeric values indicating the level of alertness, enjoyment, and demand for focus, respectively. - Face_Detection shows whether the user’s face was detected (0 = No, 1 = Yes). - Emotions such as resmasknet_anger, resmasknet_disgust, and resmasknet_fear, among others, were analyzed with probabilities ranging from 0 to 1. The same emotions were detected using an SVM model with variables like svm_anger and svm_happiness, among others, where 0 indicates the emotion was not detected, and 1 indicates it was detected. - Physiological parameters include Temperature in degrees Celsius, EDA in microseconds, and BVP in nanowatts. - The HeadBandOn variable indicates whether the Muse 2 headband was correctly used. - Brainwave data are measured in absolute power bands for delta, theta, alpha, beta, and gamma waves at locations TP9, AF7, AF8, and TP10, with values ranging from -1 to 1.75 Bels. Finally, the RAW_TP9, RAW_AF7, RAW_AF8, and RAW_TP10 variables represent raw EEG values in microvolts detected at each brain location.