Continuous Monitoring of Psychosocial Stress by Non-Invasive Volatilomics

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Psychophysiology

Background:

• Current stress detection methods (e.g., questionnaires) are subjective and unsuitable for long-term monitoring.
• Existing physiological biomarkers (e.g., HRV, cortisol) have limitations for real-time, non-invasive monitoring.
• There is a need for objective, real-time, non-invasive stress detection tools.

Purpose of the Study:

• To investigate the potential of breath and skin volatile organic compound (VOC) fingerprinting as non-invasive stress biomarkers.
• To develop a prediction model for stress-related VOCs.
• To assess the feasibility of using VOCs for real-time stress monitoring.

Main Methods:

• Induction of acute stress using the Trier Social Stress Test (TSST).
• Measurement of heart rate variability (HRV), cortisol, and anxiety levels.
• Collection and analysis of VOCs using Gas Chromatography-Mass Spectrometry (GC-MS) and a sensor array.
• Development of a prediction model for stress-related VOCs.

Main Results:

• A prediction model identified eight stress-related VOCs with up to 78% accuracy.
• A gold nanoparticle-based sensor detected significant differences in breath VOC fingerprints between stressed and non-stressed states.
• VOC levels changed during and after stress induction, indicating dynamic metabolic responses.
• VOCs showed correlation with cortisol levels, suggesting complementary information for stress detection.

Conclusions:

• Volatile organic compounds (VOCs) show promise as objective, non-invasive biomarkers for real-time stress detection.
• VOC fingerprinting can differentiate between stressed and non-stressed individuals.
• This approach could lead to novel tools for well-being monitoring and early detection of stress-related diseases.