Published November 16, 2020 © GPL3+

A Looking Glass Into the Unconscious

"Aha, a looking glass into the unconscious!" - Carl Jung. You can easily get it and get even more!

IntermediateWork in progress10 hours688

Things used in this project

Hardware components

LED (generic)

Resistor 221 ohm

Resistor 22.1k ohm

Speaker: 0.25W, 8 ohms

Resistor 100 ohm

Software apps and online services

Arduino IDE

Story

Thelong way from K.G.Jung to contemporary polygraphists. The progress isevident, but maybe something important and essential is lost? Let'stry to be clear and sort things out with Arduino.

"Aha,a looking glass into the unconscious!" - Carl Jung

Ifyou have interest,Arduino board, some cheap components, patience to understand severalsimple but fundamental regularities, then you have the opportunity tohave at your disposal no less impressive equipment and method, asJung had.

THESTORY IS ABOUT SERIOUS LOOK TO ELECTRODERMAL ACTIVITY OF HUMAN SKIN– THE MOST POPULAR PSYCHOPHYSIOLOGICAL REACTION DURING MORE THAN 100YEARS.

Fig.1. C. G. Jung

The scientific study of Electrodermal Activity (EDA) began in the early 1900-s. One of the first references to the use of EDA instruments in psychoanalysis is the book by C. G. Jung entitled Studiesin Word Analysis, published in 1906. Jung and his colleagues used the galvanometer to evaluate the emotional sensitivities of patients to lists of words during word association. Jung was so impressed with EDA monitoring, he allegedly cried, "Aha, a looking glass into the unconscious!" Jung described his use of the device in counseling in his book, and such use has continued with various practitioners.

What was the methodology, and what was the hardware that Jung and his followers were working on? The first to discover the influence of mental conditions on the galvanometer was Professor Tarchanoff, who published a paper inPflugers Archiv fur Physiologie, 1890, entitled “GalvanicPhenomena in the Human Skin in Connection with Irritation of theSensory Organs and with Various Forms of Psychic Activity”. He employed tubular unpolarizable clay electrodes, connected with the skin by means of hygroscopic cotton pads, 10 to 15 cm long, saturated with saline solution. These are attached to a Meissnerand Meyerstein galvanometer.

Fig. 2. Mirror Galvanometer, 1858

Deviations of the mirror were noted through a telescope upon a scale three meters distant from the galvanometer. The scale was divided on each side of the zero point into 50 cm, and these again into mm. The galvanometer was so sensitive that a nerve-stream of a frog sciatic nerve deflected the mirror so much that all the divisions on the scale were passed over. The electrodes were applied at various times to different portions of the body, such as the hands and fingers, feet and toes, the face, the nose, the ears and the back.

Note that this was the time of pre-electronics and pre-computers. But we have some records of this time from the book of Jung.

Fig. 3. EDA graph from Jung book

Let's leave this for a moment and see what happened when the electronics came in. Look picture from Wikipedia (Electrodermal activity).

Fig. 4. Wikipedia - Electrodermal Activity

And a record from a modern polygraph:

Fig. 5. Electrodermal Activity in Polygraph

Pretty similar, isn't it? Which is more accurate, which is more in line with reality? It turns out that it is not so easy to answer unequivocally to such a question. You have to try to understand the essence of things. But first - another record - now from my project using Arduino and Processing.

Fig. 6. Electrodermal Activity - my graph

Again a similar, only as if clearer and more definite image. And now we will deal with the substance in great detail, and yet briefly.

First of all, the basic question arises. Is any of these 4 (Fig.3 - Fig. 6) pictures real? Does at least one of these pictures show what electrical processes take place on the skin under the electrodes? The answer is: clear and definite – no! And then, do we know in theory, and can we record practical what's going on there? The answer is – yes! The following picture shows my raw registration of EDA using an Arduino.

Fig. 7. Raw registration of EDA (Arduino, Processing)

What it is? It is induction of the alternating voltage generated by the continuous electromagnetic fields of different frequencies and strengths on the inter-electrode resistance of human skin, it is also called measurement noise. This is what makes high-quality biological signal recorders very complex and expensive devices, such as all electrocardiographs, electroencephalographs, electromyographs, and also polygraphs closer to ours - devices that perform a highly standardized and certified lie detection process.

How do you fight it? And this, as we shall see immediately, is directly related to my project.

First of all, it was necessary to place a person in a special metal cage to record high-quality electrophysiological parameters, and it was absolutely necessary only some 30-40 years ago. It is also part of my personal scientific experience.

But the main thing has always been, and still is practically the only one today - it is extremely sophisticated electronics. With the help of various filters, it performs the main task of separating the useful signal from the noise by amplifying it very strongly beforehand, and then transmitting it either directly to a writing device or for in-depth analysis to a computer.

As a rule, the computer receives already filtered and purified information.

So, to better understand the novelty of my project, let's show this process in the form of the following block diagram: 1) RAW SIGNAL ---> 2) AMPLIFICATION ---> 3) SEPARATION FROM NOISE ---> 4) COMPUTER PROCESSING ---> 5) DISPLAY. In our examples (Figures 4 and 5) data are obtained directly from this scheme.

And now let's ask ourselves an intriguing question. Why are Jung's records (Fig. 3) clean? The answer is unexpected - a clear image was provided by the inertia of the mirror galvanometer cable - its ability to oscillate in phase only with the most slower changes in skin electricity, but not with the rapid harmful AC potentials. Although scientists themselves probably did not know it at that time, it was a successful coincidence that enabled them to make fundamental discoveries.

And now – directly back to my project. Once more the same intriguing question – but why my records (Fig. 6) are clean? I do not use inert galvanometer as Jung. I also don't have any electronic wonders as a polygraph. If we look at the block diagram, then we see that nothing else remains - it is achieved only by means of a computer program.

Then one has to ask - if it is already possible to obtain such clean and informative data with computer alone, then why is the effort and money spent on creating all these extremely complex electronic biopotential-s amplifiers?

The answer is very unambiguous - computer is too slow. Your instinctive reaction more likely will be a definite protest - it can't be! And now we are back in my project. Well, we have to understand now what is slow in this particular case, what is fast, what is a lot, what is a little. and then at least the options available to Jung will be in your hand. What's more, your chances will be much higher!

At this point, the question becomes very specific - what exactly do we want to record and understand? Whether this is possible in principle, and what specific paths are the best. Simply and clearly - we want to understand our spirit, our emotions, our subconscious by means of signals created by the body, which can be objectively registered for us. This signal is an orientation reaction, or specifically its vegetative component, the activity of the sympathetic system, which is highly correlated with the activity of the sweat glands on the human hands and feet.

Sweating can be measured in many ways, but the most common is measuring skin resistance or conductivity. We stick to it. And therefore, although very briefly, it is necessary to understand specifically - which processes in the sweat gland function correspond to the EDA curve.

Fig. 8 Human skin (Wikipedia)

The skin is thick, but only its top - the stratum corneum has a high electrical resistance. But it is penetrated by the sweat glands. The resistance of the horn layer itself practically does not change as result of temporary emotional changes that interest us. The sweat glands work discretely - sweat is not distributed in an even flow, but in the form of individual portions, which take place synchronously in all the glands of the region.

The formation of one portion of sweat and the subsequent its discharge through the sweat gland outlet is electrically reflected as a single galvanic reaction of the skin (specific component of Electrodermal Activity (EDA)). The expansion of the outlet opening causes a sharp drop in resistance, followed by a slow, exponential narrowing of the channel, which has little to do with the processes of interest to us - it depends almost entirely on the elasticity of the skin. This development of the change in electrical resistance over time (my attached graph, Fig. 6) is of such a characteristic shape, and it cannot be confused with anything else, it is easily visible to the naked eye.

And now - a very fundamental methodological question - how many measurements (reference points) should we have so that we can perceive this process optimally and adequately with our own eyes and understanding, in order to get the right information about process of our interest. If we are not particularly interested in the so-called latent period at the moment, then practice shows that it is quite enough for us to postpone the results graphically once every 200 - 1000 ms, i.e from 1 - 5 times per second. This is confirmed by virtually most scientific research in this field.

With a simple program, by means of Arduino Uno, we can get up to 4000 measurements per second, so - 800 measurements in 200 ms and 2000 measurements in 0.5 sec. And this proves to be quite sufficient to obtain a very high quality EDA record, and could be used as a basis for many different deeper self-knowledge and self development programs, both portable devices and computer screen projection programs with Processing. My range of such programs reaches dozens.

Fig. 9. Raw and integrated EDA (example 1)

Fig. 10. Raw and integrated EDA (example 2)

Fig. 11. Rae and integrated EDA (example 3)

As a demonstration that in this way the EDA curve is completely removed from the harmful layers, I will show some images. The distance between the red points of the integral curve is 0.5 sec. You can clearly see and count 25 oscillations between the 2 red dots, which is natural, because the main part of this harmful induction is the interference caused by the electrical network, and that is - 50 Hz.

Technicalrecommendation. These images (Fig. 7, 9-11) are obtained by transferring non-integrated data to a computer, i.e. each Arduino measurement is transferred. This is not really done wisely, and here this technology is used only to obtain these demonstration images. In real work, this is done in different way - the primary data processing is performed with Arduino, and the already processed data are sent to the computer - once every 200-1000 ms. It is happening better, safer, cleaner. It works on many my programs, some insights of which can be found in the accompanying pictures.

Fig. 12. Graphically separated active (red) and passive (green) EDA phases.

For example, with the help of the program (Fig. 12) we can easily observe these active and passive phases graphically - red bars indicate the active phase, green - passive. The more stress, the more red, and consequently fewer green bars.

Fig. 13. Internal Peace Index - a dynamic numerical relationship between the active and passive phase of the EDA.

Fig. 14. Internal Peace Index as Biofeedback tool

Such phase separation open possibility to divide the whole measurement time into two parts - active and passive, allowed to create several special stress resistance cognition and training programs (Fig.13, 14).

In conclusion, I would certainly like to say that we are left out of the discussion with many physical, biophysical and psychophysiological details. This is done so that this description does not become unreadable. Note that we only touched on the very surface of the process. The electrical phenomena of the skin are actually very versatile, profound and intriguing. If there are such conditions, I will tell a lot about it and demonstrate it in other projects.

Due to the volume, I also will not continue the analysis: from Jung to the present day - whether something important has not be lost. Answer: is lost, and this is clearly demonstrated by facts, analysis of scientific works, measurements, calculations. I hope to do this gradually in future projects.

To show that the above considerations are based on reality, I will show one concrete apparatus with a specific program:

DYNAMIC STRESS LEVEL INDICATOR

Device has a standard plastic housing with two electrodes on the upper surface on which to place two fingers of one hand. There are 10 LEDs, five red, and five yellow on the upper surface. That is all that is relevant to this particular project. Since this device is intended for the implementation of many similar programs, it contains a few more switches, in addition to inputs, outputs, etc., which I will not specifically describe here.

Fig. 15. ALGAL16 - Equipment for registration of some Psychophysiological Reactions, including EDA in action

The readings change once every 200 ms. The program calculates the average EDA level and always remembers the previous EDA data. If the current value (skin conductivity) is higher than the previous value, then a spontaneous EDA is considered to be fixed in this measerement. The program counts the number of spontaneous reactions in 10 measurements period and shows it as follows: if a spontaneous EDA is fixed for all 10 seconds, no light comes on. If this spontaneous EDA is detected for 1 in 10 seconds - nine lights are on, so all five are yellow and the left four are green. And so on. Finally, if there is no spontaneous reaction in a single measurement, then all ten lights are on - this is the maximum quiet state that can be recorded according to this ALGAL16 program. In addition, the lower the tension (stress), the lower the sound

CAUTION!

Both theoretical materials and equipment are created for self-education purposes only. They are not intended for diagnostic or therapeutic purposes, and cannot be used on other people, everyone can try it only on themselves, taking all possible risks. If someone were interested in building a more widely applicable and certifiable device on this basis, then I would be interested in different types of cooperation.

THE SOFTWARE AND HARDWARE ARE PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE AND HARDWARE.

Code

Code for "A looking glass to unconscious"

/*
#include "pitches.h"
int melody[] = { NOTE_C4, NOTE_G3, NOTE_G3, NOTE_A3, NOTE_G3, 0, NOTE_B3, NOTE_C4};
int noteDurations[] = {4, 8, 8, 4, 4, 4, 4, 4};
*/

const int  buttonPin = 13;    // the pin that the pushbutton is attached to

// Variables will change:
int buttonPushCounter = 0;   // counter for the number of button presses
int buttonState = 0;         // current state of the button
int lastButtonState = 0;     // previous state of the button

unsigned long laiks;
int punkts[210];
float sum1=0;
float sum2=0;
float sk1=0;
float sk2=0;
float kods=0;
int skaitstot=0;
int iepriepr=0;
int iepr=0;
float pulss=0;
float skrr=0;
float sumrr=0;
int n=0;
int notikums=0;
int lampuskaits=0;
int rr[20];
int setpoint=750;
int skaitsvirs=0;
int skaitszem=0;
float vidrr=0;
float videjaispulss=0;
float skaits1=0;
float summa1=0;
float videjais1=0;
float jaaa=0;
unsigned long laiks1;
float summa;
float skaits;
float tagad=0;
float tagad1=0;
int cikls=0;
int spont=0;
int iepr1=0;
int iepr2=0;
int iepr3=0;
int iepr4=0;
int iepr5=0;
int iepr6=0;
int iepr7=0;
int iepr8=0;
int iepr9=0;
int iepr10=9;
int skana=0;

int spontskaits=0;
float kgrdemo=0;
int tagadsek=0;
int kgriepr=0;
int kgrtagad=0;
int kgrdelta=0;

int kots=0;
int atslega=0;
int kotsmots=55;


#include "pitches.h"
int melody[] = { NOTE_C4, NOTE_G3, NOTE_G3, NOTE_A3, NOTE_G3, 0, NOTE_B3, NOTE_C4};
int noteDurations[] = {4, 8, 8, 4, 4, 4, 4, 4};

unsigned long laiks0;
float videjais;
float agr=0;
float starp=0;
float koef=0;
int bloks=0;

void setup() 
{
  pinMode(12, OUTPUT);
  pinMode(11, OUTPUT);
  pinMode(10, OUTPUT);
  pinMode(9, OUTPUT);
  pinMode(8, OUTPUT);
  pinMode(7, OUTPUT);
  pinMode(6, OUTPUT);
  pinMode(5, OUTPUT);
  pinMode(4, OUTPUT);
  pinMode(3, OUTPUT);
  Serial.begin(9600);
Serial.begin(9600);
}



void loop ()
{


// ###################################################################
// SĀKAS ASTOTĀ
// ###################################################################

while (1==1){ 

laiks0 = millis();
summa=0;
skaits=0;
do { 
tagad = analogRead(A2);
skaits=skaits+1;
summa=summa+tagad;
}
while (millis() - laiks0 <200);
tagad = summa/skaits;
Serial.println (tagad);

 digitalWrite(3, LOW); 
 digitalWrite(4, LOW); 
 digitalWrite(5, LOW); 
 digitalWrite(6, LOW); 
 digitalWrite(7, LOW); 
 digitalWrite(8, LOW); 
 digitalWrite(9, LOW); 
 digitalWrite(10, LOW); 
 digitalWrite(11, LOW); 
 digitalWrite(12, LOW); 

if (tagad>150){
spont=0;
if (tagad>iepr1){spont=spont+1;}
if (iepr1>iepr2){spont=spont+1;}
if (iepr2>iepr3){spont=spont+1;}
if (iepr3>iepr4){spont=spont+1;}
if (iepr4>iepr5){spont=spont+1;}
if (iepr5>iepr6){spont=spont+1;}
if (iepr6>iepr7){spont=spont+1;}
if (iepr7>iepr8){spont=spont+1;}
if (iepr8>iepr9){spont=spont+1;}
if (iepr9>iepr10){spont=spont+1;}

if (spont==0) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   digitalWrite(6,HIGH);
   digitalWrite(7,HIGH);
   digitalWrite(8,HIGH);
   digitalWrite(9,HIGH);
   digitalWrite(10,HIGH);
   digitalWrite(11,HIGH);
   digitalWrite(12,HIGH);
   }
 if (spont==1) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   digitalWrite(6,HIGH);
   digitalWrite(7,HIGH);
   digitalWrite(8,HIGH);
   digitalWrite(9,HIGH);
   digitalWrite(10,HIGH);
   digitalWrite(11,HIGH);
   }  
if (spont==2) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   digitalWrite(6,HIGH);
   digitalWrite(7,HIGH);
   digitalWrite(8,HIGH);
   digitalWrite(9,HIGH);
   digitalWrite(10,HIGH);
   }    
if (spont==3) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   digitalWrite(6,HIGH);
   digitalWrite(7,HIGH);
   digitalWrite(8,HIGH);
   digitalWrite(9,HIGH);
   } 
if (spont==4) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   digitalWrite(6,HIGH);
   digitalWrite(7,HIGH);
   digitalWrite(8,HIGH);
   }      
if (spont==5) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   digitalWrite(6,HIGH);
   digitalWrite(7,HIGH);
   }     
if (spont==6) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   digitalWrite(6,HIGH);
   }
   if (spont==7) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   digitalWrite(5,HIGH);
   }
   if (spont==8) {
   digitalWrite(3,HIGH);
   digitalWrite(4,HIGH);
   }
   if (spont==9) {
   digitalWrite(3,HIGH);
   }
   if (spont==10) {
   }
  
skana=map(spont,10,0,1000,100);
  tone(2, skana, 100);
  delay(1);  

}

iepr10=iepr9;
iepr9=iepr8;
iepr8=iepr7;
iepr7=iepr6;
iepr6=iepr5;
iepr5=iepr4;
iepr4=iepr3;
iepr3=iepr2;
iepr2=iepr1;
iepr1=tagad;
  
} // beidzas if 1==1

// ################################################################
// BEIDZAS ASTOTĀ
// ################################################################


} // beidzas "void loop ()"

Credits

Alberts Aldersons

1 project • 1 follower

Retired psychophysiologist, scientist, dr. habil. med., defended 2 dissertations, have 100+ publications. Arduino - since 2016.

A Looking Glass Into the Unconscious

Things used in this project

Hardware components

Software apps and online services

Story

Schematics

Schematics for "A looking glass to unconscious"

Code

Code for "A looking glass to unconscious"

Credits

Alberts Aldersons

Comments

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A Looking Glass Into the Unconscious

A Looking Glass Into the Unconscious

Things used in this project

Hardware components

Software apps and online services

Story

Schematics

Schematics for "A looking glass to unconscious"

Code

Code for "A looking glass to unconscious"

Credits

Alberts Aldersons

Comments

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