JPRS ID: 10638 USSR REPORT LIFE SCIENCES BIOMEDICAL AND BEHAVIORAL SCIENCES

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1~(1R ()I~H'I('IA1. lltil~: ONI.Y
JPRS L/ 10638
7 July 1982
USSR Re ort
p
LIFE SCIENCES
BIOMEDICAL AND BEHAVIORAL SCIENCES
(FOUO 4/82)
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JPRS L/1063~
7 July 1982
USS R REPORT
LIFE $CIENCES
BIOMEDICAL ANn BEHAVIORAL SCIENCES
(FOUO 4/82)
CONTENTS
~ ARTIFICIAL INTELLIGENCE
Ob~ect Deacription and Recognition in Arti~icial
- Intelligence Systema 1
BIOCHEMISTRY
Van der W~als Forces of Interaction Between Spheric~~l Aeroaol
- Particles and Cylindrical Fiber an Particlea Ap~xoach
the Fiber 3
BIONICS
- Nonlinear Information Channela 7
Introducti~n to Electroecology............� 9
Structure of, Algorithm for Estimatixig Stimuli in
_ Inetantan~oua Percept3on 14
BIOTECHNOLOGY
Distribution, Homology and Cloning of Cryptic Plaamids of
- BacilZus Thuringienais 19
~ Mobilization of Chromosomal Genes of Vibrio Cholerae ~y
Plaamid ItP4::Mu cts62 29
Radiophysical Method far Demonatrating Temperature
Abnormalitiee in Human Internal Organs 38
Cloning and Identif ication of the Gene of Hum,+an Leukocytic
Interferon Uaing Synthetic Oligonucleotides a~ Primer
and Probe 42
- a- [TII - USSR - 2].a S&T FOUO]
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_ MEDICINE
Ftorafur, an Antineoplastic Agent............�.����������~��~��� 47
Intensive Proceseing of Medicinal Raw Materials a9
- Scientific Labor Organization ir. Pharmaceutical Production...... 53
PHYSIOLOGY
Physiology and Hygiene of Pereonal Protection Against Cald
for Man 57
- Review of Book on Sleep and Motor Activitym...........o......... 62
Review of Book on Emotional Memory aiid It6 Mechaa.iams........... 67
RADIATION BIOLOGY
Industrial Hygiene and Preventi~n of Occupatianal Pathology
Related to Working With LasE:rs 72
Reaction of Proliferative and Iteating Tunor Cella to Periodic
Pulsed Ultraviolet i~ow-Intensity L~aer Radiation 76
HUMAN FACTORS
Uee of Aigital Computers for Evaluation of Operator Output...... 80
Use of Phyeiological Information in Man-~Iachine Systeme......... 85
PSYCHOLOGY
Psychological Science in Socialist Countries.......~......�.�.�~ 108
General Principlea of Peychology 111
Psychosomatic Correlations in Chronic Emotional Stress.......... 115
Source and Geneais of Mental ~~age (Gnosiological Analysis~..... 121
,
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FOl~ OFFICIAL US~E C1NLY
ARTIFICIAL INTELLIGENCE
, UAC: 621.391.19
~ OBJECT DESCI~IPTION AND RECOGNITION IN ARTIFICIAL INTELLIGENCE SYSTEMS
Moscaw ~JPISANIYE I RASPOZNAVANIYE OB"YEKTOV V SISTI~IAKH ISKU~STV3I~NOGO
INT.ELLEKTA in Russian 1980 (signed to press 30 Jun 80) p;, ,
[Annotat{.on, foreword and ~able of contents from book "Description and
Recognition of Objects in Artificial Intelligence Systems", edited by
V. S. Gurf ir~k~l', doctor of inedical sciences, and V. S. Fayn, candidate of
engineering sciences, Institute of Information TranEmitting Problems,
USSR Academy of Sciences, Izdatel'stvo "Nauka", 2300 copies, 137 pagesj
[Text] This c.ollection consists of articles dealing with the following three
problems: mathematical modeling of variability of objects that are of
- practical interest (speech process, some types of images, etc.), use of
mathematical methods in medicine and some aspects of voice control of
- cnmputers in man-machine aystema. It is intended far specialists in the
~ield of artiilcial intelligence, pattern recogniric~n and allied fields.
Foreword
- Time has ~ade appreunderstandingto�nitsnsubstancetand placet~n modern~ of
image recognition,
~ scientific engine~ring knowledge.
One of the main manifestations of this developtnent is the increasingly clear
realization that the problem of recognition propex is, tn a certain senr~e,
secondary to another problem, that of demonstratiing and describing the
essence of variability of ~he object to be identi:Eied. In all three cases
where the essEnce of variabiiity i.!~ well-atudied, organiza~ion on its basis
of an identif~c:ation process is now a rather well-studied matter. Construc-
tion of a description of variabili?__y is also of anot nerndroblem in~the
~ recognition, since it opens the way for solving P
- field of artifi.cial intelligence, that of artificial generation of change8Al1
in an object (design, v~rbal syntheais, sutomatic multiplication, etc.).
this has resulted in publica~io:~ of many works in recent years that deal
with mathematical modeling of the patterns upon whict~ a certain variable
phenomenon or object is based. This tendency has also been manifested in
this collection: the articleYebypYeP nomarev~andnYuV~NS�Prokhor v, AV.SN.
~ Omel'chenko and V. S. F~yn,
1
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F~Q n~Fr~i s e~ rcF nNr v

' 5orokin, A. P. Vaynshtok deal with the search for descriptions o~ the patterns
cliciracterizin~ object variability in diverse problems of pracrica~ importance.
Unfortunatley, demonstration of the essence of variability or ita relaLion to
externally observed characteristics of an objec:*. is a very diff icult problem,
~nd to this day it is not always solvable. A classical example is referable
to the problem of seismic forecasting or zoning. Medical diagnostic probltms,
which are also extremely difficult, are 3ust as important. However, the urgent
need to solve them is a powerful stimulus for conatantly applying mo?-e and
more efforts. In this collection, the articles of A. M. Alekseyevs;kayP~ anc
V. S. Pereverzev-Orlov, P. Ye. Kunin and V. P. Karp, Yu. B. ~ogel'son daal with
these problems.
Another problem of artificial intelligence touched upon i.n thi.s collection is
referable to organization of dialogue in a man-machine f~ystem. Making the
machine capable of understanding vocal commands is one of the mEans of
satisfying the requirement of maximum convenience and naturalness of man's
function in such a system. Research, which has been pursued in this direction
for several years, is the topic of articles by S. N. Krinov, V. P. Savel'yev,
G. I. Tsemel', as well as A. V. Vasil'yev, S. S. ~taksheyev and V. M. Chizhkov,
and S. M. Shevenko.
~ No doubt specialists in the field of pattern recognition and forecasting wi~ll
be interested in the originality of the proposed method~ and timeliness of
Eopics discussed.
Contents Page
Foreword 3
Determination Qf Empirical Relationship Using Une-Aimension,al ~
Functions (Ye. F. Yurkov, V. S. Nagornov) '
Method of Transforming Flat Curyes Based on Sliding Da~~un Method 15
(A~ S. Omel'chenko, V. S. Fayn)
Local Evaluation of Informativenesa of Flat Curve (A. S. Omel'chenko) 27
Adaptive Linear Filtration of Verbal Signals (Ye. P. Ponomarev, 32
Yu. N. Prokhorov) 42
Mechanics of Tongue Movemente (V. N. Sorokin)
Evaluation of Imperviousness to InLerf erence of Rejector Analysis of 72
Speech (A. P. Vaynshtok)
The 'Two Physician' Pr~blem in Patt~rn Recognition, . 75
(M. A. Ale~kseyevskaya, V. S. Pereverzev-Orlov)
Method of Retrospec~:ive Randomization for Comparing Efficacy of 85
- Treatment Alternatives (P. Ye. Kun~n, V. P. Karp)
Reduction of Sorting in Construction of Distinguishing Taga 89
(Yu. B. Fogel'son)
Significance of Changes in Fundamental Tone Frequence to Automatic
Speech Recognition (S, N. Krinov, V. P. Savel'yev, G. I. Tsemel') 92
Grouping of Words According to Features of Basic [Accented?] Sound~ 100
and Sound Combinations (S. N. Krinov)
Autonomous Determination of Word xags (A. V. Vasil'yev, 107
S. S. R~ksheyev, V. M. ~hizhkov~
Com~uter 'Comprehensi~n' of Textr~ in N~tural Languages (S. M. Shevchen~CO)113
COPYFiIGHT: Izdatel'stvo "Nauka", 1~80
10,657
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BIOCHEMISTRY
UDC: 539.612
VAN DER WAALS FORCES OF INTERACTION BETWEEN SIPHERICAL AEROSOL PARTICLES AND
CYLINDRICAL FIBER AS PARTICLES APPROACH THE FIBER
Moscow DOKLADY AKADEMII NAUK SSSR {n Russian Vol 26Q, No 5, Oct 81
(manuscript received 8 May 81) pp 1189-1191
~Article by I. Tashpolotov, B. F. Sadovskiy and Zh. T. Tekeraov, Physicoehemica3
Sc~entific Reaearch Institute imeni L. Ya. Karpov, Moscow]
~Text] It was demonstrated in a paper [1] dealing with aerosol filtration
theory that Van der Waals forces may play a considerable part in deposition .
of aerosols on filter fibers. On the other hand, it is necessary to know
the force of interaction of aerosol particles with c;~lindrical f ibers in order
to run processes of. regeneration of varioua fibrous filters. The forces of j~~-
teraction of these solids are discuased in i~; 2], withoult consideration of
electromagnetic lag. However, in the course o; de~osition of aerosol particles
' on the surfaces of iilter fibers, interaction forces also play an appreciable
role at distances in exces~ of 0.1 um. In this case, the hypothesis advanced
by London, to the effect tl�iat each atom instantly reacts to the fluctuating
electric field of an~ther atom, cannot be considered, ~srrictly speaking,
correct, as was demonstxated by Casimir and Polder [3]. According to [3],
at distances in excess of 0.1 }im, interaction energy is determined by
the law of 1/r~. Interaction of molecular foraes between a apherical particle
and a cyllndrical f iber ~ad not been previously examined with consideration
of the lag effect.
- According to the results in [3], the energy of interaction betwra~en two con-
densed bodies (sphe-re and cylinder) can be expressed as the imtegral of
attraction energy:
E _ - j J ~~n~xrf dV~dV=, (1)
v, r'
where V1 nnd V2 are t'~e full volumes of the sphere and cylinder; n2 and n~ are
the number of atoms per cm3 0� thsse bodies; KZ~ is London~s constant; r is the
dist?~ice between cent2rs of dVl 3nd dV2. The adequacy of such an approach
was discussed in [4, 5].
Let us transfor~,n integr~l (1) into ~he following form:
- 3
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B dV,dVi
E= f f
,
~ ~ ~2)
1f y y: /
where B= a~ E En~n~JrCd!�,
t~
~ 1. Let us conaider integral (2). By integrating respectively in the cylindri-
cal and spi~e:ic~l systems of coordinates for elP.mentary volumes dVI and dV2,
with considerati~n of the integration limits (see Figure 1), we shall obtain:
E _ _ 4B f R ~ R'R ~ ~ ~R ~ (D - R)~ j ls ! _ 2 I + ,1 !ss 1 x ~3~ ,
' aD ~ R r(S 3 S 5 S l
U-R~ R-Ra
- R~ +r= - ,R3 .
X arccos dR di,
2Rr
where ,S ~ r= t !2 . . ,
Integral (3) is not integrated in elementary functions. Calculation thereof
is made by numerical methods.
However, if Z-~ after making aimple calculations, from (3) we shall obtain
the value of energy of interaction between the sphere and an infinitely long
cylinder, with conaideration of the molecular force lag effect:
~ 16BRz 4Ri -4D~ -7DR~ -3R~
E = 15D ~ l2 ['Ra -(D+R~)~~~ +
D= +DR~ -4R= 4R= -4D= +7DR~,-3R~ ~4~
+ 8R2 [R2 -(D+R~)=j 12 (R= -(D-R~)=]=
_ D= - DR~ --4R~ D D=- (R~ +R=)~
- + In
8R= [Ri -(D-R~)~J 16Ri D= -(Rs _R=)~ .
2. In order te assess the o~tained equations, let us assume that R1 and R2 ~ H
~ (Figure 1). Then formula (4) can be approximated for energy of interaction
between the bodies in question as follows:
BR ~
E= 4~ ' RR+R= or E=45N2 ' if Rz
. w?~ere R~ = R~ is the radius of the sphere. ~5~
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For interaction force with considera-
tion of (5) we shall have:
a ' ~ ~ tl p = ~R` , ~6~
R Rj 45h(~
, On the other hand, the force of mole-
r cular attraction between a sphere
b R~' and flat surface should, according
R ~ to Deryagin [6], be proportionate
, to sphere R~ radius:
--F-- F = 2nRcF~~+ (7)
' R ~
where E(H) is the energy of interaction
~ R~ tl between two infinite plates per cm2.
N ~
D This energy according to Lifshits [7]
_ _ is de termined by the formula:
Figure 1. _ _ .
Diagram of interaction between sphe- _ p c ~ Eu - 1
- ( ) ~o(eo) . (8)
rical aerosol particle and cylindrical 3H~ 240 eo
f iber �
where h and e have the usual meaning, Eo is the electrostatic dielectric
constant and ~(eo) is a function whose value is determined from a graph.
rrom (7) and (8) with known physical parametere of a quartz lzns (EO = 3.6; R~ _
26 cm [6]), for the force of interactior,i between the lens and a flat surface
we can obtain: '
F ~ 7,19 ~ llp-1e, H'a (9)
From formula (6), taking the value of const~ant' B for quartz from [6], ;ae get:
_ . (10)
r'~'~ 3.47�10''".y-',
Thus, the force of interaction between a sphere and flat surface calculated
with formula (6) is about one-half the force as determined with formula (7).
In order to obtain a more precise value we must take into consideration the
other terms contained in (4).
3. According to [1], the condition for complete deposition of particles from
the zone of molecular attractian has the following appearance:
u < G ~R H . (11)
m? i
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~
~
where u is the velocity of the particle in the zone of attraction, p is the
length~of filtering stirface along current line and n is gas viscosity~
Let us;consider the following instance: the radius of a gold particle R1 =
10-4 cm, the radius of glass f ibers R2 = 10-4 cm, p= 5�10'2 cm, B= 2.3�10-19
erg�cm, H= 10-4 cm, then we shall have, from condition (11), u, ~2>
where Y' Q') is called a(Hell-Mann-Low) function
. ~Y (I') = AI'2 + BI'3 + CI'4 + . . . , ~3)
A, B a:td C are coefficients of axpansion.
If the system is not characterized by one parameter of order, but several--
S02i Sok~ Sop--a set of values I'Z appears with fQUrtYc-order terms.
C~nsequently, a system of nonlinear differential equations appears, i.e.,
the problem of phase transition amounts to a problem of theory of nonlinear
- fluctuations. Solving the equations enables us to determine the nature of
~ phase tranaition in the system. It can be either continuous (second c?.ass,
_ i.e., parameter of order So is not continuous at the phase transition point)
or in steps (first class).
If an electromagnetic information channel is being considered, So is the
amplitude of electric and magnetic f ield in the wave,S~ = E2 + H2; if it
is a biopolymer channel, So is the amplitude of the elastic wave.
Biophysical communication channel: If a biopolymer communication
channel is being considered, there can be interferences in it due to the
~ eff ects of high-frequency electromagnetic radiation. Tuning out the noise
- involves an increase in signal energy, i.e., its input amplitude. If there
is a stepp~d phase transition in the system, it is related to softening of the
coherent p~honon mode of the polymex chain [2, 3]. But then we are in the
region of the spectrum,�an which linked phonon states--solitons--can arise,
i.e., tuning out from the interference leads to a change in channel operating
- mode with insignificant change in input power. Now the signal can be trans-
mitted in the form of solitons [4], which are resistant to the effects of a high-
frequency electromagnetic field. Thus, we are able to change the nonlinear
channel to a different, more stable operating mode.
BIBLIOGRAPHY
1. Yevtikhiyev, N. N. and Savchenko, M. A., DAN, Vol 254, No 4, 1980, p 824.
2. Kiselew., Ye.S., Migley, M. F., Mpskalenko, S. A. and Khodzhi, P. I.,
"Tez. X Vsesoyuzn. konf. po kogerentnoy i nelineynoy optike" [Summaries of
~ Papers Deli.vered at lOth All-Union Conference on Coherent and Nonlinear
. Optics], Kiev, 1980.
3. Devyatkov, N. D., UNF, Vol 110, 1973, p 453.
4. Yevtikhiyev, N. N., Jr., TEORETICH. I MATEM. FIZ., Vol 45, 1980, p 142.
COPYRIGHT: Izdatel'stvo "Nauka", "Doklady Akademii nauk SSSR", 1982 .
_ 10,657
CSO: 1840/212
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- INTRODUCTION TO ELECTROECOLOGY
Moscow WEDENIYE V ELEKTROEKOLOGIYU in Russian 1982 (signed to press 7 Jan 82)
pp 2-7, 335-336
[Annotation, foreword by Academician V. Ye. Sokolov, introduction and table
of contents from book "Introduction to Electroecology" by Vladimir
Rustamovich Protasov, Anatoliy Ignat'yevich Bondarchuk and Vladimir Mendelevich
O1'shanskiy, Institute of Evolutionary Morphology and Ecology of Animals
imeni A. N. Severtsov, USSR Academy of Sciences, Izdatel'stvo "Nauka",
1800 copies, 336 pages]
[Text] This monograph outlines the range of problems in a new direction,
electroecology--the science dealing with electric correlations in living
nature--on the example of fish, which are animals with high electric sensi-
bility and capacity to generate electric f ields. The following are discussed
in this work: history of the question, status of the problem, analytical
methods of evaluating electric fields of biological ob~ects, questions of build-
ing the physicomathematical apparatus adequate for problems of electroecology,
and it also evaluates the effects and aftereffects of natural and artif icial
electric fields on ichthyofauna. The book is intended for a wide range of
specialists--ecologists, ichthyologists, cyberneticists, bionic engineers and
workers in the field of environmental protection.
Foreword
The book, "Introduction Into EZectroecology," is an original piece of research.
The authors did not limit themselves to a description of the existing situation
in this young branch of ecology, rather, they devoted much attention to develop-
ment of adequate physicobiological approaches to the problem. Although the
entire study is referable to ichthyology and was conducted on the class of
fish, the interaction models proposed by the authors could extend to other
classes of animals with further development of ecology.
Not only is there discussion of electric interactions between fish and
between fish and the geophysical environment, but emphasis is laid on questions
of possible effects on f ish of electromagnetic sources of anthropogenic origin.
Of course, not all of the issues are presented equally well, and this is in
part attributable to the existing situation in the scientific literature. At
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i
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the samr. time, the significant am.ount of physicomathematical lay-outs appears
logical for this branch of ecology in view of the complex nature of the problem.
This book will be of definite interest to a wide r_ircle of biologists and
t~chnic.31 specialists concerned with problems of environmental protection.
Introdur_tion
Among the intensively developing branches of biology, in addition to genetics
- and molecular biology, we can mention ecology, the science dealing with the
way of life of plants, animals and man. In our days, this discipline is
undergoing a sort of rebirth. This is related, on the one hand, to technolo-
gical progress, with which different forms of human endeavor become ecological
factors; on the other hand, it is related to appearance of new methods of
studying intrapopulation relations as a result of develo~ment of allied branches
of science. For this reason, the newly arising problems and approaches to
their solution form a new branch of ecology. The appearance of chemical
ecology (see book by M. Barbier, "Introduction to Chemical Ecology," Mir,
1978) is attributaUle ro expressly these circumstances.
It became possible for new branches of ecology to appear only as the
result of interaction between ecologists and specialists in allied disciplines.
Electroecology, an introduction ta w~iich is discussed in this monograph~
is no exception to the foregoing. Electroecology is a young and very important
branch of ecology. Electricity as an ecological factor is of interest, not
onl~ because of the enormous quantity of electric fields of anthropogenic
origin, but their involvement in orientation and communication of some f ish.
The uniqueness of electric perception inherent in the.se .fish has inspired
= scientists in different speciaities to learn all abost i,_.
When one speaks of electroperception, one occasionally uses the words, "they
see": "fish see the world by means of a new sense (see, for example, T. H.
Bullock, 1973, 1974). And, although electric perception of fish is closer,
let us say, to acoustic perception than i~c is to ~~i�:..~1 perception with
regard to a number of features (morphology o= receptors, distribution of
receptors, frequency range, informativeness, etc.), use of the word, "see,"
appears to be quite natural. At the same time, we cannot fail to note that
there is a substantial difference in ability of researchers to study vision
and to study electric perception, a difference that refers not so much to the
fact th_:St the principles of construction of these receptor systems are differ-
er_~ (Bullock, 1973), as to the fact that the researcher (man) does not have
personal experience in electroperception and cannot directly (i.e., without
the help of instruments) monitor a spontaneous or experimental situation. No
matter how great the differences between human and animal vision, in most
cases we are able to see the signs that have appreciable ecological significance
to animals, for example, geographic and time-related distinctions of the
background, coloration and changes (mating, seasonal) in coloration of animals
and plants, bioluminescence, etc. Qualitative comparisons of human and
animal visual skills (sharp-sighted eagle, blind mole, night vision of the
horned owl) were made long before determination of the physical natiure of light,
be�ore studies of physiology of vision, long bc~fore development of special
instruments.
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But when we try to assess ttie ecological significance of low-frequency electric
systems of fish, we have not experienced such direct perception and we are
compelled to proceed solely from accumulated theoretical conceptions and ex-
perimental data, and conducting experiments usually requires rather complex
equipment.
With such a situation, we need not be surprised at the abundance of physico-
mathematical calculations and physical models, or the profusion of technical
terms inherent in the literature on the topic of "Investigation of the Role of
Electric Fields in ~he Life of Fish." A number of technical ideas were dis-
cussed in biological literature much earlier than in technical literature proper.
For example, the idea of active electrolocation and physical model corresponding
to this idea were published in the JOURNAL OF EXPERIMENTAL BIOLOGY in 1958
(Lissman, Machin), whereas one of the first patents for electric location was
issued in the United States t"o (V. Shvan) only in 1971, with priority as
of 23 January 1967 (U.S. Patent No 3562633 class 324-1), i.e., almost 10 years
later.
The book, "Introduction Into Electroecology," was written with refere~nce ta
fish, which are animals with exceptionally high electric sensibility thaL
use their bioelectric fields in ecology.
However, the scientific importance of the results of studying electroecological
relations, which were pursued on f ish, is not limit~a to this class of animals.
In recent times, there has been increasingly frequent discussion in the scien-
tific literature of the possibility that various animals use electromagnetic
fields in ecology (see, for example, the book by A. S. Pressman, "Electro-
magnetic Fields and Living Nature, Nauka, 1964; Yu. A. Kholodov, "Man in
11 On the basis of the hypotheses of these
the Magnetic Web," Znaniye, 1975).
authors which, unfortunately have as yet had little experimental validation,
one can consider electroecology in a broader aspect, as a branch of biology
concerned with various types of electromagnetic correlations. In this case,
there is validity to consideration of electromagnetic interactions between
~erent animals and plants, in the first place; in the second place, it
becomes necessary to study the effects of the electromagnetic background of
the environment on ontogenesis and, in the third place, to study some pilysio-
logical functions with the use of electromagnetic fields (ENIF) on the cellular,
organismic or population levels. In this respect, the mathematical approaches
developed for fish can also be used for other classes of animals.
At the same time, electroecology is faced with ichthyological problems.
Perhaps electric ecology will be one of the keys that will enable us to
- comprehend such complex problems as homing, interspecific and intraspecific
coordination of fish.
This book is only an introduction to the problem, but aside from the broad
spectrum of examples of electric interaction of fish, it devotes much atten-
tion to attempts at quantitative analysis, engineering estimates of electric
fields, interaction between specimens via this communication channel.
The engineering estimates, construction of mode~s and quantitative estimates
conform to the modern requirements of science and enable us to understand
ii
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;
1
the pr'~nciples involved in the fucntion of some ecological systems. Thus, the
probler~ of electric ecology is discussed from different points of view in
this book. For this reason, it addresses itsel~ to a~ide circle of special-
ists--E:cologists, ichthyologists, cyberneticists and bionic engineers--who
will f:Cnd here the history of the question and can assess the status of the
problem, as well as extract the mathematics involved in evaluating the
ad,jacent zones of electric fields and consider the influence of electric
fields of surrounding background on the ichthyof auna.
This m~~nograph was written by a team of authors: Introduction, Chapter 1(History
~ of the Problem) and Chapter 2(Status of the Problem) by V. R. Protasov, doctor
of biological sciences; Chapter 3(Construction and Methods of Estimating the
Mathematical System [Software?] Consistent With the Tasks of Electroecology) by
A. I. Bondarchuk, candidate of engineering sciences; Chapter 4(Bionic Assess-
ment of Electrocommunication Systems of Fi~h) by V. M. O1'shanskiy, ~unior
scientist, and Chapter 5(Assessment of Effects on Ichthyofauna of Electric
Fields of Abiotic Origin) by V. R. Frotasov and V. M. O1'shanskiy.
Contents Page
3
Foreword 4
Introduction (V. R. Protasov) 8
Chapter 1. History of the Problem (V. R. Protasov) 22
Chapter 2. Status of the Problem (V. R. Protasov) 22
1. Informational (signal) relations in the fish class 33
2. Electricity in the life of f ish 34
3. Structure and function of electric organs 53
4. Electric f ields in schools 5~
5. Perception of electric current by fish 77
6. Electric fields as communication signals 84
7. Electric fields as orientation signals 91
- 8. Evolution of electric systems 96
Conclusion
Chapter 3. Evaluation of Electric Fields of Biological Objects on
the Basis of Theory of Linear Parametric Field of 98
PotPntials (L. I. Bondarchuk)
1. Introduction 101
2. Formulation of problem
3. Analysis and formulation of linear parametric field of 105
potentials 134
4. Metric relations on potential f ield
5. Generalized coefficients of interaction of inedia with 142
electromagnetic field 153
6. Examples of calculating electric field of soft sources 174
7. Synthesis of complex potential transfer f unctions (PTF) 182
8. Electric models and calculation of f ish f ield 2~2
Conclusion
Chapter 4. Bionic Assessment of Electrocommunication System of 203
Fish (V. M. O1'shanskiy) 204
1. Static dipole
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2. Dynamic dipole 223
3. Energetics of electrocommunication in dipole approximation 237
Conclusion 26~
Chapter 5. Assessment of Effec~s on Ichthyofauna of Electromagnetic
Fields of Abiotic Origin 269
1. A,mbient electromagnetic field. Correlation between elements
of background in water and air (V. M. O1'shanskiy) 269
2. Effect of natural electric fields of oceans on ber.avior and
distribution of fish (V. R. Pratasov) 276
3. Effects of electric fields of anthropogenic origin
(V. R. PrAtasov) 290
4. Possible aftereffects of permanent weak electric fields on
hydrofauna (V. R. Pro tasov) 308
Conclusion 321
Bibliography 323
COPYRIGHT: Izdatel'stvo "Nauka", 1982
10,657
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i ~
STRUC'i�[JRE OF ALGORITHM FOR ESTIMATING STIMULI IN INSTANTANEOUS PERCEPTION
= Moscow AVTOMATIKA I TELEMEKHANIKA in Russian No 4, Apr 82 (manuscript received
- 20 Jan 81) pp 50-53
[Article by L. M. Shcherbanskiy (Kurgan)]
[Text) ~ao variants of units are discussed, which reproduce
an algorithm for estimating the number of stimuli p~erceived
= instantaneously. These devices have sensors, a set of random
delays and multi-input OR logic circuit. Determination is
made of probabilistic characteristics of reliability of estimat-
ing the number of delivered stimuli, and operating speed of the
= units is evaluated. It is aiaintained that the algorithm run
in these units has featur es that are similar to the main
characteristics of biological sensory systems.
The study of sensory systems raises the question of simulating instantaneous
perception. It is known that man can estimate with high reliability a small
number of elements of images (for example, points or spots) presented for
- a short period of time [1].
As the number of stimuli is increased (over 6-7) reliability of estimation
diminishes. Analogous properties have been demonstrated in the cutaneous
analyzer, auditory analyzer and others. It can be assumed thate~tiesrofer-
ties of the same algorithm are the basis for similarity of prop
these analyzers. Simulation of this algorithm is of intereat to both
physiologists and engineers.
Analysis of the processncernintathenpropertiespof~thenalgorithmtfordestimating
following hypotheses co g .
~ fhe number of stimuli.
In the first place, this algorithm is unrelated t~o acanning of outputs of all
.fibers of an afferent nerve. At least 103 s would be required to scan~an
entire nerve for estimating the number of delivered stimuli, the interroga-
tion time constituting on the order of 10'3s.perfiber and there Leing on the
order of 1�106 fibers in the optic nerve. The visual analyzer esmi~matof the
~ number of delivered stimuli in tenths of a second, consequently,
processing of information about number of stimuli occurs simultaneously
(in parallel).
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In the second place, the algorithm in question is stochastic, since in estim~t-
ing the number of stimuli (for example, white [light] dots) the analy~er gives
an undetermined answer, and with increase in number of stimuli the probability
of correct estimation diminishes.
Let us consider two types of units that run the algorittm that can serve as ~
model of an unknown algorithm th~t exists in biological analyzers. Both units
are based on the use of a principle known in engineering of transforming a
_ set of simultaneously (in parallel) delivered signals into a sequence of
signals. Figure 1 illustrates the flowchart of such a un~t.
The analyzed complex signal, which containa several atimuli, is fed to the sensor
field. Each sE:nsor S simulates in this case the functions of a receptive field
[2, 3]. The g~neral requirement is that the sensor must react to different
values of the sfiiuzulus in a binary code. For this, the sensor must contain a
specialized input converter and threshold element. The apecialized input
converter transforms the stimulus into an analogue. In simulating, for example,
the visual analyZer, ph~toelectric pickups (photoresistors, photodiodes) can
serve as such a converter.
~I
S D , ~ ~et
3
LS D , 4
OF sa
S D RC ~
U ,
~ 20 40 60 s0 k
Figure 1. Figure 2.
It is further assumed that each stimulus act~vates only one sensor. The case
where each stimulus (for example, a light spot) activates a group of receptive
fields can be examined within the limits of the proposed algorittun, but is not
- discussed in this article. Sensors S that form the sensor field are connected
to delay components D. The outputa of all delay components axe connected to
the inputs of the OR circuit. A recording counter RC for the number of signals
is connected to the output of the OR circuit. Nerve fibers can be considered
an analogua of delay components, whereas the functions of the OR circuit and
recording counter are presumably performed on higher levels of the nervuus
system.
_ In analyzing the first variant of the unit, we shall consider that lag time T,
provided by each compor~ent is a discrete random value. Let us assume that
the values of all delays are in the ['[1, '[2] range and that in this range there
are k possible discrete values--gradations of lag time.
Let us examine the operating cycle of this unit. A limited number of stimuli
is delivered to the sensor field within a short time (exposure time). Since
15
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tli~ st'~nuli are distributed at random over the sensor field and the values of
delay cbmponents connected to the sensors are chosen at random, there will be
separat'ion of the signals in time.
A sequence of pulses will appear at the output of the OR logic cir~uit, and
their number is recorded by means of a small capacity recording counter.
There is a probability that is other than zero that all signals formed by the
activated sensora will be delayed for different time intervals and that the
number of inputted stimuli will be recorded in the counter. This probability
is related to the number of gradations of time lag, as well as number of
stimuli.
Pm p~ '
~ 1
0,9 0,9 '
p,g k=30 k=f00 O,B
o, ~ o~~ y=a,or y=o,aos.
~ 0,6 0,6
2 4 6 B m S 2 4 6 B fO m
Figure 3. Figure 4.
The probability that all sigr.als will have diff..rent delays, in the case of
total number k of gradations of lag time and m number of inputted signals,
can be determined using the following formula (see Appendix):
m
kl r l ~1~
Pm a(k-m) ! 1 k 1'
Figure 2 illustrates a family of curves plotted for several values of m t~s a
function of k number of gradations. Figure 3 illustrates the probability of
correct estimation Pm as a function of number of inputted stimuli, with k�.50
and k = 100.
Analysis of these functions shows that with a small number of sti~ul3 (m0.5), but then, with increase
in m, it diminishes rapidly. Such change in Pm is similar to the corresponding
functions demonstrated in biological sensory systems [1].
However, the time of estimating the number of stimuli is a more important
characCeristic. The time in which the operating cycle is effected is determined
by T2. The main reatrictions are i:mposed on T2by the resolution of the RC. The
counter's resolution is determined with the following formula:
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s~-T, ' (2)
r-k > Ts,
where k is the number of gradations, '[P is the resolution of the recording
counter (minimal time between two signals that the counter can atill perceive
separately).
In view of the f act that '[1>0 and k>0, this inequality can be converted into
T2>kTp. According to this inequality, the duration of the measuring cycle of
the unit in question is determined esaentially by the number of gradations
and resolution of the RC (i.e., it does not depend on the number of sensors).
Let us dwell in greater detail on this property of the algorithm under dis-
cussion. If we take 10'3 s as the resolution of the RC (i.e., commensurable
with the response time of a single neuron), with 100 gradations one can esti-
mate the unit's response time at 10'1 s, which is commensurable, for example,
- with the speed of action of the visual analyzer, as determined in tachistoacopic
experiments. Thus, analysis of this algorithm shows that its most important
features resemble those of sensory systems.
~ From the standpoint of a physiologist, the assumption that the lag time is
discrete :ts a very gross error. To eliminate it, let us discuss an analogue
unit, in which the time lag for each component can assume any value in the
range of ['[1i 't2]. Let us aasu~r~e that time lag is a continuous random value
, that is uniformly distributed o~~er [T1i '[2]. In thls case, restrictions on
the interval laetwee:ri delayed f~ig,t~als are also imposed by the resolution of the
recording counter. We shall give the resolution as a share of interval [T1, TZ]:
- - ( 3 )
'[p~"( ~T:-'Cf~ r
where 0 o ~
~�QB of this physiological state of cells
~.b [3]. Bearing this in mind, it is
o�N' 46 ~ a].so iritcresting to compare the be-
~ b~ q4 ~ havior af resting and proliferative
~aZ cells after exposure to lasers. This
~ o was the second ob~ective of our study.
A ~ ro- ~o" ro" m" ro., .
~E, J/cm The culture was irradiated 72 h after
Figure 1. plating, when there were 4-5�105 cella
Change in DNA synthesis (measured in (proliferative cells) per vial or
decays/min, with results aormalized after~l0 days (reating cells) when
to the control) after exposure to there were 106 cells per vial. The
periodic pulsed laser at 271 nm irradiation technique was described
- in resting (1) and proliferative (2) in [1]. Radiometry was used to
cells study the intensity of incorporation
of labeled precursors of DNA and
- RNA synthesis (~H-thymidine and 14C-uridine, respectively), .permeabtY~ty of
cell membranes for these precursors under normal cond itions and after exposure
to lasers, adhering to the methods deacribed in [4].
We used a BUF-15 mercury lamp as noncoherent source of UV light = 254 nm),
which was focused with a quartz lens at a focal distance of 12 cm. The dose
rate constituted 0.06 mW/cm2 in the plane of the bottom of the vial with
cells. A shutter [obturator] was used (10- and 100-fold attenuation) to
reduce the mean energy of radiation to the required level.
We tested the effects of the second harmonic of the copper laser (a = 271 nm)
on HeLa cells with.change in radiation dosage from~5�10'6 to 2�10'2 J/cm2.
Both DNA synthesis and permeability of the cell membrane to the ~H-thymidine
precursor of DNA synthesis were found to be sensitive to this type of radia-
tion (Figures 1 and 2). We faund that there were opposite reactions by
proliferating and resting cells. In the case of pro liferative cells, DNA
synthesis (Figure 1) was depressed over the entire range of doses we tested,
i.e., the larger the dose, the greater the depression of DNA synthesis. There
was an analogous reduction in permeability of the cell membrane to 3H-thymidine
(Figure 1). In the case of resting cells, we observed an increase in DNA
synthesis with the same range of doses (Figure 1), and it reached a maximum
~ with a dosage of 5�10-'' J/cm2. With further increase in dosage, the rate of
DNA synthesis decreased to the control level. There was concurrent increase
in permeability of the cell membrane (Figure 2), with a maximum at approxi-
mately the same dosage (5�10'4 J/cm2). �
RNA synthesis turned out to be a process with little aensitivity to radiation
by the second harmonic of the copper laser at a a 271 nm, although there is
RNA absorption, like DNA, at this wavelength. Incorporation of 14C-uridine
77
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remained at the control level uver the
- entire range of doses (f rom 5�10- 6 to
o~ 2�10' 2 J/cm2) in both proliferating and
~ ;p ~ resting cells.
0
L{B To.compare the photobiological effects
v
N S6 . of periodic pulsed W radiation to W
~ radiation from a continuous source,
~~4 ~ we conducted experiments under exactly
1~ ` the same conditions using low-intensity
~{z continuous light (BUF-15 W lamp). Un-
L~0 ~ / for~?:unately, its maximum radiation
(a = 254 nm) does not coincide exactly
~ qe ~ y with the wavelength of the second
~ harmonic of the copper laser _
~ ~
~ 46 _ 271 nm), but this wavelength is still
--'~=Z'~ in the range of nucleic acid absorp-
~ 4q ..._,t-271
tion. As can be seen in Figure 3, the
r+4t changes in DNA synthesis in prolifera-
~
~ tive and resting cells under the in-
" ~v ` ~0' !d ~o"
E, J/cm` fluence of noncoherent W light were
essentially the same: it remains at
_ Figure 2. the control level with low doses and
Change in membrane permeability for is depressed with increase in dosage.
3H-thymidine after exposure t~ periodic No stimulation phase is observed.
pulsed laser at 271 nm (1--resting Permeability of the cell membrane for
cells; 2--proliferating cells) and 3H-thymidine diminishes monutonically
after exposure to continuous W light with increase in radiation dose in
at J~ = 254 nm (3--resting cells, 4-- the case of proliferating cells,
proliferating cells) whereas in resting cells, it presents
mild (within the range of the error
factor) tendency toward increase with
_ - law doses, which changes to depression
~~Z when the dosage is increased
(Figure 3).
a.~'i ~ (0
> u As wE~ see, the reaction of prolifer-
, ~ o Qe ating cells to radiation is similar
o~ Q6 ~ for both periodic pulsed and con-
v tinuous UV light: with increase in
q~ Z dose, DNA synthesis and permeability
~ of the cell nnembrane to 3H-thymidine
z~ 4~ decrease. The findings are quite
A~ different in the case of r~sting
" id ~o ~v' ia' ~o , cells: noticeable dependence of both
E, J/c9i procesaes on seimulation dosage with
Figure 3. exposure to periodic pulsed source
Change in DNA synthesis after exposure and no stimulation with exposure to
to continuous UV light at 7~ = 254 nm W lamp. Thus, it can be coneluded
(1--resting cells, 2--proliferating) that, aside f rom the different reac-
tions of resting and proyiferative
cells to radiation from a periodic pulsed source, restin~ cells have a specific
78
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response to this type of radiation: DNA syn~:hesis is stimulated and there is
tncrease in membrane permeability to 3H-thymid:�.ne.
Unlike the data submitted above, it was possible to stimulate DNA synthesis in
proliferating cells by exposing them to powerful ultrashort picosecond pulgptl
[1]. A comparison of the data given here to the results in [lJ leads to the
conclusion that pulsed radiation in the same dosage but different form (inten-
sity, pulse duration, recurrence frequency) can elicit difierent responses in
cells. Apparently, this is attributable to the fact that in one case [1]
there is a two-quantum excitation process and in the other (Cu laser) a
single quantum process. This conclusion is also confirmed by the results we
obtained here when proliferating cells were e~posed to W light: a decrease
in DNA synthesis also dependent on dosage, without stimulation phase. We have
. yet to determine the mechanism of stimulation of DNA synthesis in resting cells
' in this light. We can only as~ume that it is a specific response of resting
cells to periodic pulsed irradiation.
Thus, there are three conclusions:
1. Exposure to periodic pulsed lasers at 271 nm elicits a change in DNA
synthesis and permeability of cell membranes to 3H-thymidine, the pracursor
of DNA synthesis, in both proliferating and resting cells. There ~s a
qualitative difference between reactions of resting and proliferating cells~
2. Period~c pulsed laser raciiation induces dose-dependent depression of DNA
synthesis in proliferating cells. Continuous W light has an analogous effect
on proliferating cells.
3. Periodic pulsed laser radiation induces a dose-dependent stimulation of
DNA synthesis and increase in permeability of the cell membrane for 3H-
thymidine in resting cells, whereas ex~osure to the same doses of continuous
UV light do not elicit stimulatiun. Evidently, stimulation of nNA synthesis
and increase in permeability of the cell membrane are related to the periodic
pulsed nature of radiation.
The authors are grateful to A. N. Zherikhin and V. I, Mishin for ttieir assistancE
in the work with the Cu laser, as well as to V. A. Semchishen and Ye. V.
Yudakhina for help in conducting the experiments.
BIBLIOGRAPHY
l. Karu, T. I., Kalendo, G. S., Letokhov, V. S. et al., KVAN~OVAYA
ELEKTRONIKA, Vol 8, IYo 12, 1981. .
_ 2. Gavosto, F, and Pileri, A., in "Cell Cycle and Cancer," New York, 1971,

~ pp 99-128.
3. Y~pifanova, 0. I., TSITOLOGIYA, Vol 21, 1979, p 1379.
4a Aleksandrova, Ye. V., Kalendo, G. S., Semenyak, 0. Yu, and Serebryakov,
P. G., TSITOLOGIYA, Vol 22, No 7, 1980, p 869.
~vr~,~IGHT: Izdatel'stvo "Nauka", "Doklady Akademii nauk SSSR", 1982
= 10,657
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HUMAN FACTORS
UDC: 658.512.011.55
USE OF DIGITAL COMPUTERS FOR EVALUATION OF OPERATOR OUTPUT
Moscow PRIBORY I SISTEMY UPRAVLENIYA in Russian No 2, Feb 82 pp 8-9
[Article by N. F. Bezhenov, candidate of engineering sciences, V. V. Kuz'mich
and P. A. Tonkonogov, engineers: "Use of Digital Computers to Evaluate.
Operator Throughput"]
[Text] One of the main elements of automated control systems for technological
processes (ACS TP) is the operator. A mandatory prerequisite for improving
the eff iciency of the entire system is to organize effective interaction be-
tween the technical part of the system and [human] operator. The important
f actors in organizing interaction include conformity of throughgut of ACS
equipment to that of the operator.
The increase in the system's throughput by means of the operator is always
minimal. The steps to increase the system~s throughput amount to selection
of people who are the most capable, training and instruction thereof. To
screen operators, on e should make an ob~ective experimental evaluation of
their output c~pacity. Output of the operator in ACS refers to the
throughput of the sensory input of the operator and speed of information
processing. Operator throughput is the reciprocal of the steepness of
reaction time to an incoming signal (tag) as a functian of amount of informa-
tion in the communication received: I/Tn., where I is the mean amount of
~ information per tag [sign] of received communication, in bits, and Tn is
reaction time in seconds.
The operator's reaction is an action that is perfo.rmed by means of man's
"output devices" (speech, movement) and the operator's motor field, which
consists of a set of buttons, keys, etc. [1]. Mainly movements are used
to transmit commands. Exper~mental studies of a number of psychologists
determined that reaction time Tn. is a linear function of quantity of informa-
tion that is average for a received tag [sign], which is a stimulus for the
operator to respond [2]. This function is expressed as follows:
Tn = to + kI ~1~
where to is simple reaction time ~lag of operator's motor resk isethe steep-
sigaal that is known in advance: but that appears suddenly),
ness of the line characterizinf; increment of reaction time T~ when the
amount of information in a co~.munication is increased.
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I ~ is i,~,l ~cv~~cl ~l~u~ Che vulue or the information received will not have an
apE>reciable influence on equation (1). Each individual operator has his "own"
inher.ent values for steepness [gradient?] k and time ta. They are minimal for
the n?ore skillful operators, and can be reduced (within certain limits) by
inetruction and training. Thus, in the course of instruction, there must be
a source of communications that permits immediate [operational] change in
amount of information in the communication, in order to check the operator's
throughput. It is expedient to use a discrete alphabet of symbols, aZ~i = m7
as such a;>u~.~rce, each of which is selected for an operator at random with
a certain probability P(a2). Every symbol in the alphabet delivers an
average amount of information, whi~h is determined by the well-known equation
for source entropy:
m
H (A) _ ~ (A) _ - ~ p (~r) ~aBs P ~a[) �
~-i
If the alphabet symbols (for example, numerals) have different laws (series~
of distribution in each experiment, the mean amount of information carried
with each symbol will differ, in particular, it will be maximal with a
uniform law of distribtxtion. The more the distribution differs from being
~ uniform, the less information is given by the source to the operator. If
symbols a2 of the alphabet are chosen for an operator N times, the time of
his reaction to the message is calculated using the formula: ~
Tn = E~t2/N
where E~ti is overall reaction time to all symbols presented to the operator
in a given test.
The Consul printer, which is the unit of outputting information from the Mir-2
digital computer, is the source.of symbols with different laws of distribution
that are presented to the operator. Discrete [digital] messages from the
source are numerals, 0, 1, 2, 7, printed on paper at random times.
Appropriate program s for the Mir-2 computer are used to generate pseudorandom
numbers that form an entire group of events.
- Four experiments with the computer are run to determine function Tn = f(I).
The series of distribution of pseudorandom numbers are approximated by the
laws of Rayleigh, normal, exponential and uniform distribution. The distribu-
tion series and ,corresponding amounts of information per symbol are listed
in Table 1.
The operator's reaction time is found by measuring the interval between ~his
response [action] and time of delivery of a stimulus (printed digit). The
responsive (controlling) action of the operator is to depress a key on the
control console, the number of which corresponds to the digit printed by the
Consul. The time interval is measured by electronic computation. The~times
at which the computer prints out the digital symbol and the appropriate
81
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button is depressed determine the leading edge [front] and cut-off [decay] of
the gate [strobe] pulse, the duration of which, '[str~ equals the measured
- interval pt. This time is measured by counting the pulses with fixed recur-
rence frequency F~ that f ill the interval. If the recurrence frequency of
counting [calculating?] pulses equals F~ (recurrence period T~) there will
be C= ~t/T~ = AtF~ within the measured interval ~t.
. Table 1.
Approximating Symbols
law of
distribution � I.~ ~ I 3 I~ I b 6 I~ Ibit
ol
~
Rayleigh o,oi o,n o,~~ o,s~a o,o5s o,o3s o.ozs o,os i,~
Normal 0,025 o,os o,v o,2sa o,zss o,n o,os o,025 z.3~
Exponential o,ss o,19 o,ia o.is o,09 o,oe o,o~s o,o~s z:es
Uniform o, isa o, izs o, i2a o, i~5 0, tzs o, tzs o, izs o, i~ 3
Table 2. Thus, the measured interval will be found
- - ~ in the following manner: Ot = C/F~ s.
operator Tnt I T~~s I T~a I T�� The number C of counting pulses that fill
the gate pulse is read by the pulse
~ I~,12 I~~~ I~ 19 I~,~y~ counter, and the frequency meter is used
~ ~,2+ in the summation mode for this purpose.
3 1,02 0.983 1.001 1.4
The experimental equipment for operator
Table 3. training consists of the following
(Figure 1): source of communications,
operator~ r. I k interval timer, operator's console with
I control unit. The Ch3-38 frequency meter
~ I o,912 I o,>� (in summation mode), combined with a
GS-15 countin ulse enerator is used
3 0.79b 0.103 g P g ~
'R, to measure the time intervals. The
generator delivers counting pulses at a
f ixed recurrence frequency to the input of the frequency meter. The unit that
controls the interval timer causes formation of gate pulses and controls delivery
of counting pulses to the frPquency meter.
The control unit consists of a set of triggers, QR and AND circuits (Figure 2).
The triggers are actuated by computer signa:.s that control digital printout.
The triggers are returned to their initial (zero) state by the operat~r, by
depressing a button on the working console that corresponds to the digital ,
~ symbol pri~nted on paper. The gate pulses thus formed pass from the trigger
uutputs through the OR circuit to the input of the AND circuit, thus causing
delivery uf counting pulses to the frequency meter input. ~If the wrong
button is depressed in error, one that does not correspond to thp printed
symbo"l, the cut-off of the gate pulse is not formed and the frequency meter
continues to measure the time interval. Steepness k of inclination [see
formula (1)] and the operator's simple reaction time to are detexmined by
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processing experimental data with the least squares method. This providea for
best conformity of experimentally obtained results with the individual capa-
cities of operators.
Operator's control console ,
C
Source of 0
- Mir-2 N Timer control Timer
computer S
information U
~ L
, Figure 1.
The experimental values of parameters Tn2 and IZ, found by the method of least
squares are substituted in the analytical express~on of the sought function (1);
_ This yields the following system of
arbitrary linear equations{3]: ~
lo-~k~~-Tni
From to-f-k~z-T,,:=0;
computer , I�-}-kla-7'u~=U;
o ~o ~-k/~-Ta ~ =0.
, _ to .
Ch3-
~ 38
' from This system is reduced to normal .equations
~
'T GS-15 of the following appearance:
~ ~
i
~ AA]to-{-~ A1 k- ATp]-0;
, f ~,,to+,~Sl,~-~~To,-o, l c2>
from work console
Figure 2. where AL = 1 is the coefficient with
time to.
[AA], [AI], [IT ] are found from the experimental data in the following
manner:
AA~ =AiAi-f-AzAs-I-AaAa-f-A~A~~
A1] =A~~i-~-As~a-1-Aa~a-f-A~~~:
ATnJ =A~Tni-I-/4zTas-~As1'ns-I-A~7'a~~
II ~ _ /i / i -~-/s/s-~-~a~~-~-1~~~c
/10 ) _ ~i T� i -F~sTu9-I-~aToa'I-~~Tn~.
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hl)It UtMlt'IA1, 11~M l)NI.Y
The values of parameters k ar~d to for each operator are found by solving system
of equations (2~.
In an experimental test of this method, laboratory technicians and computer
laboratory engineers, who had experience in working at the consoles of various
digital computers, participated as operators. There were more than 15 tested
operators in all. The results of the experiment (reaction time Tn in seconds)
were different for each participant. Table 2 lists data obtained for three
operators.
After substituting the values of parameters I and Tn in (2) and solving the
system of equations on a digital computer, we found the values for time to in
seconds and steepness k in s/bits (Table 3).
= These values could also be found by graphic plotting (approximately). Experi-
mental determination of time Tn and calculation of time ta and steepness k
make it possible to assess the individual capacities of an operator (the lower
the values c+f parameters to and k, the greaqer his throughput capacity).
Throughput of the above-mentioned operators constituted 8.55, 7.81 and 9.71 bit/s,
respectively. For other operators who participated in the experiment, there
was a 1-1.5 bit/s difference from the above figures.for their throughput.
This is consistent with the already known results of other experiments, which
confirm that man is capable of receiving and processing 0.1-10 bits of in-
formation per second [4-6]. Each subject should first become familiar with
the experimental operator console to improve the reliability of results.
Thus, use of a digital computer as the source of random symbols delivered to
an operator and elec~ronic timing of his reaction to symbols permits immediate
["operational"] evaluation of operators' throughput. This method could be
used for s~reening operators for ACS TP.
BIBLIOGRAPHY
1. Polyakova, L. V. and Leyn, V. M., "Display of Measurement Information,"
Leningrad, Energiya, 1978.
2. Maydel'man, I. N., Revenko, V. N. and Sarkisyan, B. G., "Information
Display in Automated Control Systems," Moscow, Sov. radio, 1972.
3. Vostroknutov, N. G. and Yevtikhiyev, N. N., "Information and Measurement
Technology," Moscow, Vysshaya shkola, 1977.
4. Temnikov, F. Ye., Afonin, V. A. and Dmitriyev, V. Ir, "Theoretical
Bases of Information Technology," Moscow, Energiya, 1979.
5. Trostnikov, V. N., "Man and Information," Moscow, Nauka, 1970.
6. Kostyuk, V. I. and Khodakov, V. Ye., Information Display Systems and
Engineering Psychology," Kiev, Vysshaya shkola, 1977.
, COPYRIGHT: Izdatel'stvo "Mashinostroyeniye", "Pribory i sistemy upravleniya", ~
1982
10,657
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UDC: 331.015.1
USE OF PHYSIOLOGICAL INFORMATION IN MAN-MACHINE SYSTEMS
Moscow AVTOMATIKA I TELEMEKHANIKA in Russian No 1, Jan 82 (manuscript received
16 Dec 80) pp 151-166 ~
[Article by A. A. Desova (Moscow)]
[Text] Use of physiological informatian about the state
and qualities of an operator is discussed in the areas of
design, study and oppration of man-machine systems. Groups
of specialized criteria referable to engineering psychology,
which characterize practical tasks, are singled out. The
main phases of the methodological approach to construction of
formalized assessments of physiological information are
developed and described. An ap~roach is offered to construc-
tion of a quantitative evaluation of an operator's functional
state, which i~ developed on the example of formation of the
scale of operating [working] tension.
In recent times, increasing attention has been devoted to use of physiological
information (PI) characterizing a human operator (0) in the design, study and
operation of man-machine (MM) systems. Such information is based on measure-
ment of different physiological parameters (PP), such as electrical activity
of the brain, cardiac activity, galvanic skin response, respiration, blood and
urine biochemistry, and many others.
From the standpoint of problems of engineering psychology, PI can be useful as
a gauge of two main factors: current functional state of the operator, for
example, degree of fatigue, emotional and working tension, stress, level of
waicefulness, etc.; individual psychological traits and potential capacities
of the operator.
Evaluation of these factors is very important to many practical tasks where
the results can be used for different purposes (Chart). Thus, evaluation of
an operator's current functional state is necessary primarily for t.asks
involved in assuring reliability and eff iciency of MM systems, in designing
operator work places and problems of industrial hygiene. Evaluation of
individual psychological human traits is used in the areas of vocational
screening and operator training.
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- Physiological parameters
~ ~
Gauge of operator's current Gauge of individual psycho-
functional state logical properties and
potential capacities
of operator
. ~ ~ y y ~
Checking Industrial Work Applicant Operator
operator hygiene place screening training
reliability design
The main stages in solving the problem of practical use of PI in MM systems
ar.e: elaboration of an engineering psychological criterion (for example, pro-
bability of operator error, probability of worsening of health, degree of
change in functional state., etc.) characterizing the practical problem to be
solved, which is a function of the measured physiological parameters; deter-
mination of.the most informative set of PP; developm~nt of a formalized
� method for evaluating the selected criterion in the function of ineasured PP.
Our objective here was to discuss a range of questions related with the first
and third of the above stages. We intend to provide a systematized survey
of practical tasks, for the performance of which PI are used, determine the
main criteria specific to these tasks, shed light on approaches to develop-
ment of formalized methods of using PI in current use, as well as to show
the way to further ref ine these methods.
We shall not discuss ~here questions related to investigation of the informa-
tiveness of different PP. This is a problem of great independent importance
and requires special consideration. One can find the most complete biblio-
graphy on this subject in [7, 9, 60, 73, 78, 80].
I. Areas of Use of PI in Man-Machine Systems
At the present time, the task of developing reliable and refined methods of
using PI for practical purposes is at its f irst stage. However, there have
been very many studies directed at development of such methods. Analysis of
this research enables us to single but the main promising areas and aspects
of ~sing PI.
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1. Chc~ckinA Reliability of Operator Performance
Problems of this class are referable, first of all, to systema, in which e~er-
gency situations are possible due to partial or total loss of operator work
capacity. These tasks are inherent in, for example, such sectors as cosmo-
nautics, aviation, railroad and motor vehicle transport.
Several worka have dealt with general formulation of the problem of using PI to
evaluate reliability and eff iciency of operator performance [10, 18, 32, 50, 59,
98, 68, 81, 105]. There, stress is placed on demonstration of relationships
between changes in PP and decreased operator work capacity [50, 68], determina-
tion of permissible range of changes in parameters of physiological systeme [10,
18], feasibility of forecasting operator atates [59, 10, 94] and several other ~
problems.
One usually makes a distinction in the problem of enhancing.operator reliability
between such tasks as preliminary checking of operator readiness [qualifica-
tions?] for a given job [45, 85], ongoing monitoring of the operator's functional
state, which changes under the influence of working and ambient conditions, in-
cluding extreme factors [44, 75, 78, 115J; implementation of prognostic checks
of operator work capacity so that preventive and protective steps can be
promptly instituted [10, 41, 71, 89].
Among the most constructive steps referable to monitoring operator reliability,
we can list differentiation between active waking and drowsy states according
to electroencephalograph (EEG) parameters [2, 25] and galvanic skin response
(GSR) [46, 113], assessment of degree of fatigue according to a set of para-
meters, including the EEG, EMG (electromyogram) and GSR [82], assessment of
fatigue according to statistical characteristics of cardiac rhythm [13, 53, 77],
forecast~!ng a comatose state according to changes in shape o� pulse wave [54],
diff erentiation between rest and activity according to cardiac rhythm [8] and
a number of others.
2. Evaluation of Professional Aptitude of Operators
Problems of this type are most often solved as they apply to screening special- '
ists in such important occupationa as pilots, railroad engineers, operators
of complex technological systems, etc. Psychophysiological studiea are pur-
sued in order to screen applicants that meet specific requirements for a given
type of wor~C [3, 12, 33, 45]. Use of physiological information in such tasks
is validated, first of all, by the fact that there is a correlation between PP
and a number of human psychological traits that are significant from the
standpoint of professional aptitude [suitability]. Thus, we can mention such
experimental data as presence of correlation between level of intelligence
and frequency range of evoked potentials [101], between level of vestibular
stability and parameters of base tonus of the autonomic nervous system [E],
between EMG changes during performance of perceptual tasks dealing with dis-
crimination and psychological ratings on the Eysenck scale [106], between
degree of depression of alpha rhythm with a load and level of capacities [102),
etc. The existence of such correlations makes it possible to use PP in
classifying subjects into groups according to type of nervous system and type
of physiological reactions [4, 15, 42, 76, 90, 92, 114, 122], as well as
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r~~n vrr~~~H~, voc, v~.~.~
for assessment of the following: subjects' resistance to extreme factora, for
cxample, vibration, accelerations, orthostatic load, exercise [6, 56, 79J,
level of inental [101, 102, 103, 119] and operating [93, 104J capacities,
su6$estibility [69J, degree of conditioning [11, 99], etc.
In addition to the above aspects of using physiological information in the
area of professional aptitude, w.: can mention another special area of applica-
tion [37]. It is known that test study procedures are used extensively in
problems of professional screening, which are aimed at demonstrating traits
that are professionally ~important, such as stability and ability to switch
attention, operative memory, sensorimotor coordination and a number of others.
Measurement of PP which are, in turn, a retlection of an operator's functional
state, could be aimed at refining testing methods. Information about such
aspects of functional state as degree of operating and emotional tension,
- degree of fatigue, could be useful in conducting tests in the aspects described
below.
The existing methods of assessing testing results (usually problem solving
time and number of errors) are rather poor. Information about the sub~ect's
state, particularly about his operating tension, could serve as an additional
assessment of quality of performance of a given test and, consequently, as an
additional evaluation of the tested psychophysiological property. As a result,
there is better reliability of testing as a whole, and it also becomes
possible to have a more differe~tiated gradation of the evaluation.
The ratings used in testing are related not only to the tested psychophysiolo-
gical property but, to some degree, the sub~ect's functional state (emotional
excitement, fatigue). Information about this state can be used to either
control the testing process (coiitrol of testing may consist of taking steps
to diminish emotional excitement, stopping the test if there is an inadmissible
degree of fatigue, etc.) or to Correct testing grades.
~ The above aspects of using information about the functional state of operators
require, in most cases, both qualitative and quantitative evaluation of such
states.
3. Operator Tra.ining
At the present time, physiological information is used relatively little in
tasks of this type. However, it is stressed in a number of works that use
of such information is important [22, 45, 59, 63, 70, 72, 84, 96]. Mention
is made of such purposes for its use as investigation of the learning proceas
and development of its bases [59, 72, 70, 84], forecasting quality of
training [22, 63], development of training equipment [59], etc.
This aspect of using PP is based on the relationahip between degree of operator
training and degree of his tension, which emerges as a sort of "physiological
payment" for the work results achieved. Many studies [70, 100, 110, 121] are
aimed at studying the relationships betwee*~ PP and diff iculty of an assignment.
Work difficul ty is determined by either ob,jective indicators of difficulty of
an assignment [57, 121] or duration of training to perform a given ~ob [70].
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MOR UFFICIAI. USE ONI'~.Y
The results of such studies can be used directly in operator training, both
to work out criteria of training and to refine training systems.
In addition, in training problems, information about the operator's functional
~ sCate can emerge as one of the criteria of causes of nonachievement in the
learning process. Excitement, stress, fatigue, weak activity, etc., may be
such causes. Depending on the demonstrated cause, one can add some stimulat-
ing factors to the training syst~m (incentives, assurance, etc.) in the form
of appropriate instructions to the trainee. It is believed that the use of
physiological information is particularly promising in development of
automated teaching systems.
4. Industrial Hygiene
Problems of this type are aimed at assessing the psychophysiological expendi-
tures of workers in different occupations fox~. the~ p~~pose of scientific organi-
zation of labor and providing conditions that conform to public health
requirements [43, 51].
Studies aimed at sol~ing this problem are pursued during actual work and
deal most often with such specialists as pilots [39, 40, 48, 123], air traffic
controllers [115, 116], railroad dispatchers [64], computer center workers
[17, 77], motor vehicle drivera [16], mine workers [13], etc. Most often,
the ob~ective of these studies is to assess man's physiological reactions
in the presence of neuroemotional tension [39, 40], stress occurring in
emergency situations [48, 115], phyaical loads [11, 35, 95] and fatigue [13,
16, 77, 82]. Several studiea have been made of tha effects of such working
conditions as monotony [82J, holding a strained position for a long time [49],
and studies are also made of the dynamics of the state in the course of a
work day and week [17]. Many works deal with assessment of the effects of
extreme environmental factors, particularly spaceflight factora, on changes
in operator PP [9, 18, 78, 89]. The resulta of the above-mentioned studies
can be used directly to form criteria characterizing the effects of work
factors on operators' health status. .
5. Designing the Operator's Work Place
The problem of usii.g physiological information in problems of~operator work
place design was raised in several works [5, 21, 34, 67, 72, 118, 124].
In such problems, measurement of physiological parameters permits determina-
tion of the relationship between quality of equipment and psychophysiological
input required to perform a given job. We can mention a number of studies
dealing with consideration of PI in elaborating criteria of quality of
information display systems [1, 38, 67], selecting optimum configuration of
operator chairs [124], evaluating diff iculty in driving motor vehicles
with different types of transmissions [118~, etc.
Therz are two main aspects to the practica~l use of PI in designing problema.
In the first place, this information permits direct assesament of designed
~;~stems from the standpoint of ineeting industrial hygiene requir.ements and,
in the second place, it can serve as an indirect indicator of reliability of
operator performance. Bo.th factors determine to a substantial degree the
quality of the proposed operator work place.
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hult UMMIIIA~ u~e. UNLY
Evaluation of a proposed system according to the criterion of reliability of
~,~?~~r~tc?r performance is based on the correlation between psychophysiological
[iiE,ut c~t the operator and difficulty of his work. By estimating the operator's
psychophysiological input [expenditure] (on the basis of ineasurement of PP),
one can predict the probability of errors and thereby assess the proposed
system. There are several works [57, 70J that deal with evaluation of PP
as a function of difficulty of an assignment. These results can be used
directly to form criteria characterizing the quality of a proposed system.
By virtue of the prognostic nature of this information, use of PI in this
aspect is particularly promising with respect to reducing the time of f ield
[on the job] trials of newly designed systems.
II. Methods of Formalizing PI Evaluations
~ At the present time, most studies in the area of using PI are chiefly pursued
to gain knowledge, and they are directed at demonstration of various physiolo-
gical parameters as functions (~D) of some objective indicators or other,
which emerge as engineering psychological criteria (W) specific to a given
study. This is a so-called "direct" problem whose purpose is to find the
functions:
m~~F~~W), i=1, 2,..., n~ - ~1~
where n is the number of physiological parameters.
The results of solving this type of problem are rei:lected in many works [26,
60, 73, 80, 82, 66].
However, to make practical use of PI, one must solve the "opposite" problem,
whose purpose is to construct a solving rule that permits evaluation of the
adopted criterion W as a function of a set of ineasured PP:
_ W=~ (m~, m:, m�). ~ ~2)
The solutions of these "direct" and "opposite" problems do not ensue directly
from one another, due to the heterogeneity of changes in each PP individually
as a function of the given criteria and influence of many factors on the nature
of these functions. Although most current works deal with investigation of
the "direct" problem, it is still far from having been completely solved.
There are appreciably fewer studies dealing with the "opposite" problem, and
% its solution is still far from complete. In this part of our work, our
purpose was to discuss the existing approaches to solving the "opposite"
problem.
Methodolagically, construction of function (2) amounts to proceeding through
the following main stages: elaboration of criterion W in terms of the
meaningful substance of the practical task to be performed; determination of
the aggregate of informative physiological parameters; choice of software that
would permit construction of the solving rul.e to assess the adopted criterion
as a function of ineasured PP.
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Let us consider the specifics of these stagea in greater detail.
The above survey of practical problems, for the solution of which PI is used,
enables us to single out the following main groups of specialized criteria:
criteria characterizing operator work capacity in a specified type of work
expressed in terms of results of such work. Use of these criteria is made
primarily in the area of improving reliability and eff iciency of MM systems
and design thereof; criteria characterizing the concrete psychological
traits of the operator (for example, type of nervous system, intelligence,
suggestibility, etc.) expressed in terms of the corresponding psychological
properties. Such criteria are used in professional screening and training;
criteria that characterize the effects of working and ambient conditions on
health. These criteria are used in problems of industrial hygiene,
designing MM systems, as well as problems of improving reliability of MM systems.
Apparently, within each of these groups there can be quite a few narrowly
specialized criteria determined by the specifics of a concrete practical task.
In order to obtain maximum accuracy in solving this problem, it is desirable to
form as many specialized criteria as possible. However, such an "individual"
approach is justified only for particularly important practical tasks. To
make broader use of PI, it is desirable to form a perhaps lesa accurate but
more general criterion, which could be used in various practical problems. The
functional state of the operator could serve as such a criterion, for example,
degree of fatigue, emotional or operating tension, activation, etc. However,
the absence of a strict, ~prma~ definition of the concept of "functional state,"
for which reason it is necessary to select several obj ective indicators, in
the terms of which this concept can be expressed, is a conaiderable difficulty in
the path of forming such a criterion.
Let us consider the existing approaches to methods of specifying the functional
state of an operator, which are used in experimental research. Here, we can
single out two main directions. The first one involves specification of
functional state by means of organizing the experiment. Thus, most of ten the
subject's functional state is given by such procedures as use of emotiogenic
stimuli ~14, 20, 42, 86, 87, 111], presenting tasks eliciting mental or
operating tension [4, 19, 30, 58, 73, 100, 106, 114, 12U], use of interference
while performing a specified job [57], giviug physical loads [11, 91], etc.
In such experiments, the functional state is controlled, for example, by
changing the difficulty of problems or operations, changing the noise level,
setting.time limits, etc. Occasionally, such artificial methods as dramatic
["actor"] simulation (73], hypnosis [31, 73] and pharmacological agents [88] are
used to produce the appropriate functional state.
The above methods of producing a functional state are referable to model ex-
periments. In addition, experiments are performed rather frequently under
real working conditions [16, 64, 115, 107, 117]. In this case, the nature
and level of functional state are determined by such factors as work time,
~resence of emutional factors (passing tests, complicated situation) and a
number o.f others.
With the second approach to means of setting the furictional state, indicators
of results of performance are used as a criterion thereof [29, 53, 68, 93, 100].
_ During the experiment, the subject performs a certain work (f~r example,
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wurkin~; at a bench, solving test problems, etc.), the reaults of which are evalu-
ated by several objective indicators (number of errors, solving time, etc.).
Determination is made of the measured PP as a function of objective indicators
of achievement. The latter emerge as a criterion of the subject's functional
- etate.
As for the choice of a set of informative tags, the physiological signs known
to date can be divided into the following groups: parametric signs, for example,
pulse rate as a correlate of inental tension [73, 40, 20], amplitude of EKG
waves as a correlate of inental work [19], arterial pressure as a correlate of
operating tension [57, 72), etc.; signs determined by the degree of correlation
either between different derivations of physiological signals, for example,
change in degree of correlation between bioelectric potentials of different
parts of the cerebral cortex during mental work [58J, or between different types
of physiological signals such as, for example, change in correlations between
EKG parameters, pressure and pulse in the presence of fatigue [16]; signs that
are determined by the statistical parameters of physiological processes, such
as change in spectral and correlation characteristics of R-R intervals of the
EKG in the presence of fatigue [13, 10, 53, 77J, change in mean asymmetry of
duration of phases of alpha rhythm in the presence of a mental load, fatigue
and sleepiness [2, 25], etc.
ThP choice of basic set of signs to construct function (2) is usually made
oii the basis of prevailing conceptions of informativeness of certain PP ~r
other, as well as the researcher's available technical resources. Ther~ is
often the problem of minimizing the sign space on the basis of using correlation
or factor analysis. The effectiveness of these methods in reducing the number
of ineasured signs is reflected in a number of works [3, 97, 109, 112, 47]. For
example, data are furnished that were obtained on the basis of the method of
main components to reduce the number of intormative tags (EEG parameters)
characterizing different types of rest, ranging from several tens to several
units [97, 112]. Factor analysis on the basis of examining the time series of
- R-R intervals of the EKG revealed one informative tag that characterizes pilot
tension during flights [47].
~ The next stage following the ctxoice of the initial set of inforII?ative tags
is to construct the solving rule to assess the adopted criterion as a func-
tion of ineasured PP. For this purpose, two mathematical approaches are being
used: pattern recognition method and regression analysis method. The main
distinction of these methods is that the use of recognition actually solves
the problem of qualitative evaluation of the criterion under s*~.~3y (most
often, determination of its alternate class, for example, sleep--wakefulness,
' excitement--rest, etc.), whereas with the regression model a quantitative
evaluation of this criterion is made on a continuous scale, calibrated in terms
of the corresponding objective parameters.
In the area under discussion, the pattern recognition method has the most
- application, and this is due primarily to the fact that it is less difficult to
construct a cla~sification algorithm. As a rule, the recognition method is
used to assess the current state of an operator [26, 28, 36, 55, 61, 83, 112]
and in professional screening [23, 24, 69, 79]. In most cases, recognition
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involves two alternatives. ?n the first of th.e above tasks, distinction is
~aade between such states as rest and activity [83], normal and comatose state
[54], wakefulness ard s1eF~piness [26], rest [calm] ancl emotional excitement
[20, 61J. In the area or agplicant screening, a distinction is made between
"good" and "bad" opera�ors [24], those with and without aptitude for learning
[23], resistant and n.onresistant to suggestion [69], etc. In a number of
works, a ulor~e difficult problem is solved, namely, recognitiun involving
multiple alternati~ves [112, 28]. For example, there is examination of the
_ po~sibility of distinguishing between such states as activity, operative
~ rest, drowsine~s, sleep [28]. As a rule, the classification algorithm is
' cozstructed by the method of learning with a"teacher." Here, tre f~llowing
two methods of presenting the teaching sample are used. With the first one,
the teac.hir~g sample is formed by means of obvious specification of identified
classes, ior example, specifying such states as s~eep; drowsiness, rest, or

_I certain t~pes of subjects. Not infrequently, ancillary criteria are also
used, which characterize the relevant classes.
With the secand method, there is indirect presentation of the teaching sample,
wh.ich is based on the method of setting u~ the experiment. Thus, various types
of inental ~ctivity [26J, various types of emotionally signif icant factors [61]~
various psychological tests [83], etc., are g~ven by means of experimental
conditions. In this case, the specifir_ difficulty of tize studies is that the
teaching sample is not precisely specified. For example, giving emotion211y
signif icant factors cannot a~ways unequivocally determine the subject's
- emotional reaction. This makes it necessary to increase substantially tha
size of the teaclling samQle to assure statistically rel.iable results.
When constructing the solving rule for recognition of psychophysiological
states and operator traits, the basis is quit~ ~ften referable to experimental
~ data on the properties of. the used tags. Most often, one uses the procedure
of successive ar~alysis of probabilities ttiat a given tag belongs tn a given
class [24, 26-28, 69]. This classif~cation methoc~ 3.s the most suitable in
- cases where the recognition prc;cess implies the use of additional tag analysis
_ as the diagnostic solution is ohtained. This usuai?y accurs in problems of
professional screening or identification of developing states, such as sleepi-
ness, fatigue, etc. For example, successive analysis is used [26] to make
a distinction between waking anu sleepy states on the basis of the parameter
that is defined by the mean asymmetr;~ of duration of phases of EEG alpha
_ rhythm. Elsewhere [24], determination was made of whether operat~r~3 belong
to a known good or bad class on the basis of results of psychological tests
and physiological reactions. In [69], sp~cialists were screened, who must
make important decisions, according to suggest3;bility on the basis of ineasurement
- of a set of EKG parametPrs.
In several pther works [20, 74, 83], a linear discriminant function, the
value of which characterizes the degree to which an object with given value of
tags belongs to the relevant class, is used f.or classification of states under
study. For example, this method was used to distinguish between rest and
emotional tension due to anl:icipation of an impact load, on the basis of a
set of signs such as pulse rate and arterial pres~ure [20J. A classification
algorithm was constructed [83) for the states of calm wakefulness and tensioii
due to performance of test assignemnts? on the basis of ineasuring the spectral
- characteristics of the EKG.
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fl~i~ m~tli~~d ut ~1~?~:~1t1~~~Clu~~ 15 the moet effective wti~n ttiere !s u~rni:t.l
distribution of tile tags used.
1Jse of multiple regression anaZysis is another approach to formalized evalua-
~ tion of eng~.neering psychological criteria as a function of ineasured PP [6,
108; 22, 52, 62, 65, 79, 89, 118]. As we have already mentioned, unlike
recognition methods, in this case it is a problem of, quan.titative, rather than.
qualitative, evaluatiQn. This makes it necessary to use appropriate metrics
("scales") characterizing the adopted criterion in given units of ineasurement.
- The appropriate scales are usually formed with consideration of the specific
function of the practical task. For example, we can mention studies dealing
with avaluation of vestibuJ.ar stability of subjects [6, 79], forecasting
operative work capacity [52~, evaluation of ~uality of flight training [22,
62], etc. In all cases, the problem of forming the appronriate scale amounts
to experimental determination of the set flf ineasured PP as a function (2) of
the adopted W criterion. For axample, flight achievement expressed as a
grade [22], quali.ty of performance in units of precision and time character-
istics [52J, etc., are used as W criteria.
The method of f~rmin~ function (2) consists of two successive stages: choice
of structure oi equation accurate to a certain number of unknown coefficients
and estimation of these coefficients on the basis of available experimental
, data. Selection of ttie structure of regresa~ion equation,is genera~ly lim:Lted
to construction of linear models of bott. the unknown coefficients and measured
parameters ~i. Calculation of the soughi. criterion is made in the followin.g
form:
. _ - -
1~=~io+~i,Q~,+~i:Q~=+ . . . ~f-~~4~~, ~ (,3)
where bo, b2 (i = 1, n) are estimates of coefficients of the regression
equation. These coefficients are deterimined at the stage of "teaching" th.e
model, in the course of which the values of r.riterion W~ are given (or
measured) and the corresponding v~lues of ~Z, are measured. It is assumed that
these values are related in equations of ~.he following type:
. � Wi=bo+ ~bcm~.r~"~~, 1'=1,2,...,N, 44)
whFSre W~ is the value of the criterion in the ,jth experiment; ~Z~~ is the
value of the ith parameter in the jth experiment; ~ is a random centered func-
tion which is independent of W~j and determined by t~e influence of unknown
factors on the measurement process; I~ is the number of equations.
Estimation of unknown coefficients bi is made by means of the least squares
method. The influence of interference is suppressed due to rednr~dancy of
the system of experimental cases ["observations"] (N>n).
The effectiveness of using regressfon models depends largely on the adequacy of
conditions of tlie "teaching" experiment to actual conditions, for which the
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F
O~c ~
scale is being formed. Consequently, the task of providing conformity of
"teaching" and "examination" [test] conditions is of. first and foremost im-

~ portat:ce. Althougn there are few works dealing with construction of regression
models, it is evident that this direction is promising from the positive re-
aults of a nur~ber of studies [22, 52]�
III. Mea.:is of Further Development of Methods for For malized Use of
Physiological Information
~ There are mainly two reasons for the difficulty in using PI to solve practical
problems. The first is attz~ibutable to the complexity of physiological signals
notable far such properties as time variability, similarity of reactions to
different factors, poor differentiation with regard to different states of the
body and very marked individuality. The second reason that makes it quite
difficult for practical uae of PI is the wide diversity of engineering paycho-
- logical criteria (EPC), that are spe~ific to each concrete form of ~Ctivity.
Since it is inexpedient to elaborate formalized methods of using PI
separately for each type of activity, it is necessary to form a rather
general [universal] EPC tha~ is suitable for solving many practical problems.
In this part of our work, we shall discuss one of the possible approachea
tc.~ solving such problems.
As we have already stated, the most general EPC is evaluation of the operator's
functional state. However, the absence of a formal definition of this concept
makes it necessary to choose certain ob~ective ~arameters, in the terms of
which it can be measured. In a rather ger~eral case, one can select the
in3icators of operator achievement as such ob~ective parameters. However,
the difficulty then arises that the parameters of performance are just as
.diverse as the types of activity themselves. For this reason, such parameters
must be selected in a rather abstract form.
In view of the fo~regoing, we propose the following approach to creation of a
quantitative evaluation ("scale") of functional sta~e on the example of
developing the scale of operating t.ension.
l. A certain set of "standard" problems is selected, each of which is ~~hese
terized by the specificity of psychophysiological input to solve them.
may be problems that are related, for example, to intellectual or sensorimotor
activity, etc. Eacti of these stsndard problems is used to form. the scale of
tension inherent in the corresponding type of activity (intellectual, sens~ri-
motor, etc.). ~
One must take into cr~nsideration the following requirements in selecting a
standard problem [or task].
The standard problem must have objective parameters of results of solving
it. This may be either parameters of solution quality (numbEr of errors,
solving time, etc.) or ob~ective indicators of difficulty of solution (level
of interference, limited time, etc.).
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V:iriation of conditions of presentation of the standard problem (for example,
variation of pace or duration of presentation, interference level, etc.~
should lead to a change in difficulty of solving it, which causes a char.ige in
tension.
2. A certain set of physiological parameters is selected, which emerge as
informative signs of operating tension. The scale of functional states is
formed as physiological parameters as a statistical function of quantitative
indicators of results of solving the standard prob~.em.
3. Evaluation of an operator's functional state under real conditions, which
is done by measuring his physiological parameters, is made in terms of
indicators of achievement in solving the relevant standard probl~m. For
each concrete, reaJ_ activity a set of standard problems is chosen which
corresponds the closest to the ~ob with regard to nature of psychophysiological
input required.
The method of constructing a functional state scale consists of the following.
A standard problem and method of varying operating tension during solution
thereof are selected. For exampie, tension can be varied by introducing
different levels of interference, time limits, modifying the standard problem,
- etc. This method of varying operating tension is based on the assumption that
an operator can suszain the qualit'y of standard problem solving on a constant
and rather high level with change in ob~ective d~fficulty of this problem due
to a corresponding increase in tension.
The statistical relationship between the measured PP and objective indicators
of difficulty of solving the problem, which are set by the experimental
conditions, is determined experimentally for a ratY~er large group of sub~ects
in the course of solving the standard problem. The difficul.ty of the asgignment
for each sub~ect is varied in the range of minimum diff iculty to a certain
critical difficulty, with which accuracy of performance exceeds the permissible
range. The objective indicator of problem difficulty corresponding to the
critical value is taken as 100% tension, while the corresponding values of
' physiological parameters expressed in relative amounts of background values
are taken as the cut-off values on the formed scale. Thus, as a result of
experimenting with each sub~ect, we obtain his physiological parameters as
a function of problem difficulty, which is expreased as a percentage of
~ critical diff iculty.
This experiment is conducted on a rather large group of subjects, and the
' individual results are appropriately averaged for the entire group.
The function obtained by th~ above method is used as the scale of operating
tension for a given type of activity. It should be noted that the resol~sti~~n
of this scale depends on the degree of ce:tainty of the obtained function.
Degree of certainty refers to the correlation between the full range of
changes in the measured parameters caused by change in problem difficulty and
random (including those determined by individual distinctions) variations of
the same par~ameters, that are unrelated to the work load. In some cases, it is
expedient to coristruct the scale and use it on a rather homogeneous group of
operators to increase its conclusiveness ~"def.initeness"J.
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. 1Q0
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