Assessing cognitive load in adolescent and adult students using photoplethysmogram morphometrics

Area of Science:

• Physiological computing
• Biomedical engineering
• Human-computer interaction

Background:

• Photoplethysmogram (PPG) signals, particularly from peripheral sites, show promise for cognitive load assessment.
• Existing research lacks studies on adolescent cognitive load using physiological signals and comprehensive PPG morphometric analysis across age groups.

Purpose of the Study:

• To analyze photoplethysmogram (PPG) morphometrics for cognitive load assessment.
• To compare PPG morphometric responses to cognitive tasks between adolescent and adult students.
• To investigate the efficacy of wearable physiological signals for cognitive load measurement.

Main Methods:

• Analysis of PPG signal morphological features during two-level arithmetic tasks.
• Comparison of PPG morphometrics between adolescent and adult student cohorts.
• Evaluation of physiological signals from wearable devices for cognitive load assessment.

Main Results:

• PPG morphometrics demonstrated significance comparable to heart rate in reflecting task difficulty and duration.
• Distinct morphological behaviors in PPG signals were observed between adolescent and adult students during cognitive tasks.
• Wearable physiological signals proved effective for measuring cognitive load.

Conclusions:

• PPG morphometrics offer a sensitive measure for cognitive load assessment in students.
• Observed differences in PPG morphology between age groups suggest underlying physiological variations.
• Wearable technology can reliably capture physiological data for cognitive load monitoring.