Remote detection of mental workload changes using cardiac parameters assessed with a low-cost webcam

Area of Science:

• Physiological monitoring
• Biomedical signal processing
• Human-computer interaction

Background:

• Accurate mental workload assessment is crucial for optimizing performance and safety.
• Traditional methods often require specialized equipment and direct contact.
• Developing non-invasive, remote monitoring techniques is a significant research goal.

Purpose of the Study:

• To introduce a novel framework for detecting mental workload changes using low-cost webcam video.
• To validate the framework by comparing its results with electrodermal activity measurements.
• To demonstrate the feasibility of remote, non-contact mental workload assessment.

Main Methods:

• Utilized image processing and continuous wavelet transform filtering on webcam photoplethysmographic (PPG) signals.
• Applied a Stroop color word test to induce stress in twelve participants.
• Derived mental workload from pulse rate variability and PPG amplitude fluctuations, reflecting peripheral vasoconstriction.

Main Results:

• The developed framework successfully detected mental workload changes.
• A strong correlation was observed between the webcam-derived mental workload and electrodermal activity.
• Photoplethysmographic amplitude fluctuations correlated with peripheral vasoconstriction changes.

Conclusions:

• Webcam-based photoplethysmography offers a viable, low-cost method for remote mental workload detection.
• This approach provides a promising alternative to conventional, contact-based physiological monitoring techniques.
• The findings support the use of accessible technology for understanding cognitive states.