Human Identification with their VOC Distribution Through CMS – SEN Model

Smell printing or odor printing is a novel morphological characteristic that an object can be defined by its odor. Human body odor is one such biological trait that yields less error rate of 15% among other biometrics. The human odor printing or smell printing possesses significance against the world towards screening of security checkpoint, searching for survivals under rubbles, investigating criminals, and many more. Cogno-monitoring system (CMS) is a specific prototype to furnish two essential processes -odor analysis and odor encoding through the Sensing-Encoding-Notifying (SEN) model to give the sensitivity and specificity score among the individuals. Human body odor can be interpreted as the alliance of various volatile organic compounds (VOCs) and they are recognized, classified in the encoding process. This article exhibits a detailed analysis of the traditional detection methods including bioanalysis concerning the human body human body odor experimented with 6 people. By applying principal component analysis along with random forest classifier, the VOCs distribution of the individuals is measured. This work calculates that 18.7% of VOCs are having a match with all the individuals which become the plinth for the identification of humans.

From musk to body odor: decoding olfaction through genetic variation

The olfactory system combines input from multiple receptor types to represent odor information, but there are few explicit examples relating olfactory receptor (OR) activity patterns to odor perception. To uncover these relationships, we performed genome-wide scans on odor-perception phenotypes for ten odors in 1003 Han Chinese and validated results for six of these odors in an ethnically diverse population (n=364). In both populations, we replicated three previously reported associations (β-ionone/OR5A, androstenone/OR7D4, cis-3-hexen-1-ol/OR2J3 LD-band), suggesting that olfactory phenotype/genotype studies are robust across populations. Two novel associations between an OR and odor perception contribute to our understanding of olfactory coding. First, we found a SNP in OR51B2 that associated with trans-3-methyl-2-hexenoic acid, a key component of human underarm odor. Second, we found two linked SNPs associated with the musk Galaxolide in a novel musk receptor, OR4D6, which is also the first OR shown to drive specific anosmia to a musk compound. We also found that the derived alleles of the SNPs reportedly associated with odor perception tend to reduce odor intensity, supporting the hypothesis that the primate olfactory gene repertoire has degenerated over time. This study provides information about coding for human body odor, and gives us insight into broader mechanisms of olfactory coding, such as how differential OR activation can converge on a similar percept.

Titrating the Smell of Fear: Initial Evidence for Dose-Invariant Behavioral, Physiological, and Neural Responses

It is well accepted that emotional intensity scales with stimulus strength. Here, we used physiological and neuroimaging techniques to ask whether human body odor—which can convey salient social information—also induces dose-dependent effects on behavior, physiology, and neural responses. To test this, we first collected sweat from 36 males classified as low-, medium-, and high-fear responders. Next, in a double-blind within-subjects functional-MRI design, 31 women were exposed to three doses of fear-associated human chemosignals and neutral sweat while viewing face morphs varying between expressions of fear and disgust. Behaviorally, we found that all doses of fear-sweat volatiles biased participants toward perceiving fear in ambiguous morphs, a dose-invariant effect generally repeated across physiological and neural measures. Bayesian dose-response analysis indicated moderate evidence for the null hypothesis (except for the left amygdala), tentatively suggesting that the human olfactory system engages an all-or-none mechanism for tagging fear above a minimal threshold.