In science, human thermodynamic imaging is the application of imaging technologies in the facilitative quantification of human thermodynamic parameters and quantities. The subject of human thermodynamics is the study of the energy, entropy, and work aspects of systems of humans. [1] The newly developed prototype technology of vibraimaging, according to its developers, is said to be able to quantify “emotions” of humans, such as would be visible in unconscious facial muscular expression during a typical human-human interaction. In this sense, future applications of vibraimaging technology or other advanced variants may possibly facilitate the human thermodynamic quantification of a given human-human interaction (A↔B) process:

A + B ↔ AB ↔ A=B ↔ A≡B ↔ A + B

Formula for emotion recognition and calculations
Developers of the new Vibraimage 7.0 system are calling for suggested new formulas for emotion recognition and emotion calculations, according to which Elsys could realize suggested algorithms and present systems and software for independent testing. The simplest model would attempt to quantify the measure of “affinity” A between the imaged individual and the object according to which the individual is reactive to. In a general sense, a positive affinity (A > 0) indicates attraction or proximity closure, typically visualized by pleasant emotional expressions; conversely, negative affinity (A < 0) indicates repulsion or proximity distancing, typically visualized by disturbed emotional expressions. The measure of the total reactive affinity between a set of individuals in a system is what is called “free energy”, a fact proved in 1882 by German physician and physicist Hermann Helmholtz. [2] To illustrate, a “system” of interacting humans is diagramed below, where initially entities (people) A and B are affined to each, as indicated to their close proximity:


In the chemical sense, each individual, A, B, and C, would be considered as individual "human molecules", each having different reactive affinity tendencies to each other. [3] If, in the initial state of this system, individual C were introduced into the system, whereby it was known that A had a greater affinity preference to C than to B, a spatial displacement reaction would occur, in which A displaced B to form a dynamic proximity bond with C, as would be visualized by “negative” emotional changes in the A-B interactions and “positive” emotional changes in the A-C interactions. This change is diagrammed below as the “final state” of the system after its reactive evolution:

In terms of affinity reaction diagrams, this process would be described as:

in which, for instance, as diagrammed above, if chemical species A and B are attached in a weakly bonded chemical union, signified by the bonding bracket “{“, ordered such that if species C were introduced into the system, the greater affinity preference of A for C would cause A to displace B and to thus form a new union with C, which equates to the following in modern terms:

AB + C → AC + B

These types of human “affinity” reactions were described in 1809 by German polymath Johann Goethe. In the modern “energetics” (first law) or “thermodynamics” (first and second law) sense of the human-human (A↔B) interactions, as discerned following the development of the science of chemical thermodynamics in 1882, it known that the thermodynamic measure of the affinity reactions in a system is quantified by the following expression:

A = -ΔG

This expression states that the measure of the affinity A of a system is equal to the negative of the Gibbs free energy change ΔG of the reactions in the system. In verbal translation, this means that a spontaneous process, occurring in a system of reactive humans (human molecules) will proceed when the reactions result in an overall decrease in the free energy of the system, an effect known as the "combined law of thermodynamics":

ΔG < 0

which means that the molecules have migrated towards their affinity preferences. In expanded form, where:

ΔG = ΔH – TΔS

this expression, ΔG < 0, equates to the following characterization of a spontaneous process in entropy ΔS and enthalpy ΔH terms:

A = TΔS – ΔH

In this sense, the entropy S changes (generally related to organization factors and irreversible work loses) and enthalpy H changes (generally related to physical heats and bond energies) involved in a human-human interaction process, if quantifiable, give a measure of the driving force or change in the system. In this sense, it is possible that a visual mapping of the emotions involved in such interactions may facilitate a topographical free energy mapping of a given system, such as is done with in drug-receptor interactions of systems of target molecules and proteins use in medicine. [5] To summarize, the 2003 work Information Theory and Evolution by Danish theoretical chemist John Avery gives us the correct modern interpretation of the relation of Gibbs free energy to the interactions of molecules: [6]

“When two molecules fit closely together, with their physical contours matching, and with complementary patterns of excess charge also matching, the Gibbs free energy of the total system is minimized … thus, the self-assembly of matching components proceeds spontaneously, just as every other chemical reaction proceeds spontaneously when the difference in Gibbs free energy between the products and the reactants is negative.”

In this sense, if the interactions between humans can be quantified via information modeling using computers and video imaging equipment, then possibly a correlative function can be found between the Gibbs free energy of each interaction, the Gibbs free energy change of the total system, and the resultant affinity dynamics of the individuals involved in the reactive process.

Notes
The simple model described here assumes that human-human interactions are immune to external system forces that may be acting on the system as well as flows of new individuals into the system. A more detailed analysis would take into account such factors, using an expression similar to that shown below, for the infinitesimal reversible change in the Gibbs free energy, for an open system, subjected to the operation of external forces Xi, which cause the external parameters of the system ai to change by an amount dai, is given by:

where:

μi is the chemical potential of the i-th chemical component.
Ni is the number of particles (or number of moles) composing the i-th chemical component.

This, however, is an very advanced field of research.

Version for research
Based on energy and entropy affinity models it is probable to suppose that level of two persons affinity is proportional to the level of FH normality in vibraimaging, because normal distribution has maximum entropy among all real-valued distributions according to the Gibbs measure. It is easy for preliminary testing to any Vibraimage user. You need to capture FH for one person in frame, than for both persons in frame with the same setting conditions. The level of moving FH to normal distribution will display the persons affinity. Elsys will includes level of distribution normality to FH calculation to the next reduction of 7.0 version and informs vibraimage members about this upgrade.

References
1. (a) Thims, Libb. (2007). Human Chemistry (Volume One), (preview), (Google books). Morrisville, NC: LuLu.
(b) Thims, Libb. (2007). Human Chemistry (Volume Two), (Ch. 16: "Human Thermodynamics", pgs. 653-702), (preview). Morrisville, NC: LuLu.
2. (a) Helmholtz, Hermann. (1882). “Die Thermodynamik Chemischer Vorgänge (The Thermodynamics of Chemical Operations”, SB: 22-39, in Wissenschaftliche Abhandlungen von Hermann von Helmholtz. 3 vols. Leipzig: J.A. barth, 1882-95. 2:958-78.
(b) Young, Paul T. (1936). Motivation of Behavior – the Fundamental Determinants of Human and Animal Activity, (ch. 2: “The Energetics of Activity”, pg. 68) New York: Wiley.
3. Thims, Libb. (2008). The Human Molecule, (preview). Morrisville, NC: LuLu.
4. Goethe, Johann von. (1809). Elective Affinities. New York: Penguin Classics.
5. Raffa, Robert B. (2001). Drug-Receptor Thermodynamics - Introduction and Applications (ch. 27: Thermodynamic Maps of Receptor-Ligand Pairs Reveal How Some Proteins Bond, pgs. 581-92). New York: John Wiley & Sons.
6. Avery, John (2003). Information Theory and Evolution, (pg. 174, back matter). New Jersey: World Scientific.