# Capturing Emotions Induced by Fragrances in Saliva: Objective Emotional Assessment Based on Molecular Biomarker Profiles

## TL;DR

This study introduces a non-invasive way to measure emotions caused by fragrances using saliva biomarkers, offering an objective alternative to traditional methods.

## Contribution

The novel use of salivary biomarkers to decode multidimensional emotional responses to fragrances in real-time.

## Key findings

- Salivary biomarkers like oxytocin and cortisol correlate with specific emotional states such as happiness and relaxation.
- Classification and Regression Trees (CART) analysis successfully detected emotional profiles from biomarker data.
- Validation in an independent cohort confirmed the consistency between molecular profiles and behavioral measures.

## Abstract

In this study, we describe a non-invasive approach to objectively assess fragrance-induced emotions using multiplex salivary biomarker profiling. Traditional self-reports, physiological monitoring, and neuroimaging remain limited by subjectivity, invasiveness, or poor temporal resolution. Saliva offers an advantageous alternative, reflecting rapid neuroendocrine changes linked to emotional states. We combined four key salivary biomarkers, cortisol, alpha-amylase, dehydroepiandrosterone, and oxytocin, to capture multidimensional emotional responses. Two clinical studies (n = 30, n = 63) and one user study (n = 80) exposed volunteers to six fragrances, with saliva collected before and 5 and 20 min after olfactory stimulation. Subjective emotional ratings were also obtained through questionnaires or an implicit approach. Rigorous analytical validation accounted for circadian variation and sample stability. Biomarker patterns revealed fragrance-induced emotional profiles, highlighting subgroups of participants whose biomarker dynamics correlated with particular emotional states. Increased oxytocin and decreased cortisol levels aligned with happiness and relaxation; in comparison, distinct biomarker combinations were associated with confidence or dynamism. Classification and Regression Trees (CART) analysis results demonstrated high sensitivity for detecting these profiles. Validation in an independent cohort using an implicit association test confirmed concordance between molecular profiles and behavioral measures, underscoring the robustness of this method. Our findings establish salivary biomarker profiling as an objective tool for decoding real-time emotional responses. Beyond advancing affective neuroscience, this approach holds translational potential in personalized fragrance design, sensory marketing, and therapeutic applications for stress-related disorders.