The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data
The purpose of the study is to elaborate the decision support model for medical recovery assessment by estimation of functional state of wounded and sick persons during their treatment in hospital conditions to substantiate the necessity of a further rehabilitation.
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Міжнародний науково-навчальний центр інформаційних технологій і систем НАН України та МОН України
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irk-123456789-1249922017-10-14T03:03:13Z The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data Shvets, A.V. Kich, A.Y. Медицинская и биологическая кибернетика The purpose of the study is to elaborate the decision support model for medical recovery assessment by estimation of functional state of wounded and sick persons during their treatment in hospital conditions to substantiate the necessity of a further rehabilitation. Выявлены особенности восстановления характеристик ВСР и ЭЭГ, которые заключаются в существенно худшем восстановлении функционального состояния (ФС) группы военнослужащих с контузией головного мозга по сравнению с лицами, которые не имели контузии мозга в анамнезе (соответственно 23,3% и 83, 4% лиц с положительной динамикой, p <0,001). Описаны структурные особенности 3-х ЭЭГ-феноменов, которые встречаются у лиц с контузией головного мозга. Анализ межсистемных связей ЭЭГ и ВСР дополнительно свидетельствует о медленном восстановлении ФС у лиц I группы. С помощью факторного анализа нормированных характеристик изменения показателей ЭЭГ и ВСР до и после восстановительного лечения построена регрессионная модель поддержки принятия решения с целью прогнозирования реабилитационного потенциала человека и эффективности реабилитации в госпитальных условиях. Виявлені особливості відновлення характеристик ВСР і ЕЕГ полягають в істотно гіршому відновленні функціонального стану (ФС) групи військовослужбовців з контузією головного мозку в порівнянні з особами, які не мали контузії мозку в анамнезі (відповідно 23,3% та 83, 4% осіб з позитивною динамікою, p < 0,001). Описано структурні особливості 3-х ЕЕГ-феноменів, які зустрічаються у осіб з контузією головного мозку. Аналіз міжсистемних зв'язків ЕЕГ і ВСР додатково свідчить про повільне відновлення ФС у осіб I групи. За допомогою факторного аналізу нормованих характеристик зміни показників ЕЕГ і ВСР до і після відновного лікування побудована регресійна модель підтримки прийняття рішення з метою прогнозування реабілітаційного потенціалу людини і ефективності реабілітації в госпітальних умовах. 2017 Article The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data / A.V. Shvets, A.Y. Kich // Кибернетика и вычислительная техника. — 2017. — Вип. 3 (189). — С. 79-96. — Бібліогр.: 19 назв. — англ. 0452-9910 DOI: doi.org/10.15407/kvt188.02.075 http://dspace.nbuv.gov.ua/handle/123456789/124992 616.89-07-08(035):616-036.82:355.11:355.721 en Кибернетика и вычислительная техника Міжнародний науково-навчальний центр інформаційних технологій і систем НАН України та МОН України |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
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DSpace DC |
| language |
English |
| topic |
Медицинская и биологическая кибернетика Медицинская и биологическая кибернетика |
| spellingShingle |
Медицинская и биологическая кибернетика Медицинская и биологическая кибернетика Shvets, A.V. Kich, A.Y. The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data Кибернетика и вычислительная техника |
| description |
The purpose of the study is to elaborate the decision support model for medical recovery assessment by estimation of functional state of wounded and sick persons during their treatment in hospital conditions to substantiate the necessity of a further rehabilitation. |
| format |
Article |
| author |
Shvets, A.V. Kich, A.Y. |
| author_facet |
Shvets, A.V. Kich, A.Y. |
| author_sort |
Shvets, A.V. |
| title |
The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data |
| title_short |
The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data |
| title_full |
The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data |
| title_fullStr |
The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data |
| title_full_unstemmed |
The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data |
| title_sort |
decision support model for forecasting of wounded and sick restoration in hospital conditions based on psychophysiological data |
| publisher |
Міжнародний науково-навчальний центр інформаційних технологій і систем НАН України та МОН України |
| publishDate |
2017 |
| topic_facet |
Медицинская и биологическая кибернетика |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/124992 |
| citation_txt |
The Decision Support Model for Forecasting of Wounded and Sick Restoration in Hospital Conditions Based on Psychophysiological Data / A.V. Shvets, A.Y. Kich // Кибернетика и вычислительная техника. — 2017. — Вип. 3 (189). — С. 79-96. — Бібліогр.: 19 назв. — англ. |
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Кибернетика и вычислительная техника |
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ISSN 2519-2205 (Online), ISSN 0454-9910 (Print). Киб. и выч. техн. 2017. № 3 (189)
DOI: https://doi.org/10.15407/kvt188.02.075
UDC 616.89-07-08(035):616-036.82:355.11:355.721
A.V. SHVETS1, Dr (Medicine), Senior Researcher,
Head of Research Department of Special Medicine and Psychophysiology of Research
Institute of Military Medicine of Ukrainian Military Medical Academy
e-mail: shvetsandro@gmail.com
A.Y. KICH2, PhD (Medicine),
Head of Military Medical Clinical Center of Occupational Pathology
e-mail: kikh76@ukr.net
1 Research Institute of Military Medicine of Ukrainian Military Medical Academy,
04655, Ukraine, Kiev, Melnikova Str. 24
2 Military Medical Clinical Center of Occupational Pathology of Servicemen
of Ukrainian Armed Forces, 08203, Ukraine, Kyiv region, Irpin. 11-line Str. 1.
THE DECISION SUPPORT MODEL FOR FORECASTING
OF WOUNDED AND SICK RESTORATION IN HOSPITAL
CONDITIONS BASED ON PSYCHOPHYSIOLOGICAL DATA
Introduction. The psychological unpreparedness, non-coping fear with the responsibilities,
feeling guilt to the dead, striving to survive in terms of destruction and deaths of others, ex-
treme strain of duty, violations of food recreation and other harmful factors of duty undoubt-
edly reduce the human adaptive reserves and lead to non-constructive changes of behaviors
and disadaptation syndrome that need their assessment for further rehabilitation treatment
requirement.
The purpose of the study is to elaborate the decision support model for medical recovery
assessment by estimation of functional state of wounded and sick persons during their
treatment in hospital conditions to substantiate the necessity of a further rehabilitation.
Materials and methods. There were selected two groups of 25–45 ages’ men: I group —
30 persons that got mild traumatic brain injury (mTBI) during the 2014–2015 years and had
comorbid somatic pathology, the II group — 30 people who had only therapeutic pathology.
The assessment of functional state (FS) was based on heart rate variability (HRV) and
electroencephalography (EEG) data before and after their rehabilitation treatment.
Results. The features of patients recovering based on the study of EEG and HRV charac-
teristics were significantly worse according to the functional state (FS) of individuals that had
mTBI (only 23,3 % of positive dynamics) comparing with others (83,4 %;
p < 0,001). There were described structural features of three types of EEG phenomena, which
occur in patients with mTBI. The analysis of interrelations of EEG and HRV data addition-
ally confirms a slow recovery of FS of patients with mTBI. The physiological value of FS
regulation was the highest among individuals that had mTBI.
Conclusions. The decision support model for assessment of human recovery potential by
evaluation of functional state of wounded and sick persons allows quantitatively predict the
A.V. SHVETS, A.Y. KICH, 2017
79
A.V. Shvets, A.Y. Kich
ISSN 2519-2205 (Online), ISSN 0454-9910 (Print). Киб. и выч. техн. 2017. № 3 (189) 80
need for further rehabilitation after the hospital treatment. It was shown that application of
EEG and HRV hardware during rehabilitation of combatants in hospital conditions allows to
evaluate a specific morphological defects and the degree of human rehabilitation potential.
Keywords: rehabilitation potential, participants in anti-terrorist operations, functional state,
heart rate variability, electroencephalography .
INTRODUCTION
The number of Ukrainian citizens and military personnel who need rehabilitation
is growing up due to the non-stable situation in Ukraine, especially in its eastern
part, where Anti-Terrorist Operation (ATO Zone) is conducted. The moral and
psychological unpreparedness, a distress among military personnel that cannot
be coped, striving to survive in terms of destruction and death of others, extreme
tension of labor, violations of food and recreation and other harmful factors of
work with no doubt reduce an adaptation reserves and cause non-constructive
behavioral changes and disadaptation syndrome.
It is well known that health is a dynamic phenomenon so it needs monitor-
ing. Hence, the "functional state" (FS) is widely used for detecting subtle
changes in health indicators [1, 2, 3]. The definition of "functional state" can be
used to characterize the functioning of certain organs, physiological systems and
the whole body. "Interaction of spatially distributed dynamic processes that oc-
cur in the central nervous system (CNS) and in the whole body eventually de-
termines the wide-ranging classes of psychophysiological phenomena that can
be qualified as a "state" [4].
The existing methods of monitoring of rehabilitation effectiveness are
usually based on different physical activity samples [5]. However, the presence
of complex pathology among the ATO participants (combination somatic
injuries and mental disorders) often makes the performance of such tests
impossible. Therefore, there is a need to use other effective measures to
comprehensively take into account many changes in human FS without the
physical activity usage.
One of the most common methods of human brain investigation is
electroencephalographic (EEG) study. Generally recognized criteria of dynamics
of CNS FS is frequency-amplitude characteristic of brain biopotentials. For that
reason, the stability of the dominant alpha rhythm is considered as indicator of
optimal brain function. The EEG desynchronization reflects on the increasing of
brain excitability and lability, growing the activation process up. Conversely, the
growing synchronization of bioelectrical activity with increasing amplitude and
decreasing frequency of the dominant brain rhythm indicates a reduction of brain
functions [1, 6, 7, 8].
Due to the neurohumoral and autonomic regulation of the circulatory system
as an important part of human adaptation to changing environmental factors,
there is another equally important method for the FS assessment as the heart rate
variability (HRV) examination [1]. While computed tomography and magnetic
resonance imaging scans are often normal, the individual with traumatic brain
injury (TBI) has cognitive problems such as headache, difficulty thinking,
memory problems, attention deficits, mood swings and frustration. These
injuries are commonly overlooked [9]. Even though this type of TBI is called
The Decision Support Model for Forecasting of Wounded and Sick Restoration
ISSN 2519-2205 (Online), ISSN 0454-9910 (Print). Киб. и выч. техн. 2017. № 3 (189) 81
“mild”. Thus, the EEG and HRV examination for assessing the FS recovery
during rehabilitation of wounded and sick especially with mild TBI in hospital
conditions is an urgent task of modern military neuroscience and clinical
medicine.
The aim is elaboration of the decision support model for medical recovery
assessment by estimation of functional state of wounded and sick persons during
their treatment in hospital conditions to substantiate the necessity of a further
rehabilitation.
MATERIALS AND METHODS
The 1st st group of exanimated military personnel was formed from 30 men aged
25–45 years who had mTBI and comorbid somatic pathology, and 2nd nd group
— 30 men with the same age who did not have mTBI but were treated (rehabili-
tated) due to other therapeutic pathology at hospital. The vast majority of these
people (90 %) consisted of mobilized soldiers who performed tasks in the anti-
terrorist operation area approximately one year. A control 3 rd rd group of
73 healthy men with the same age range was examined to compare the results of
the research.
Each servicemen was treated by individual rehabilitation program during
12–14 days. This course provided the best range of types, forms, capacities,
timelines of rehabilitation measures determining the order of their performance,
and it was aimed to rehabilitation and compensation of violated or lost functions
and capabilities of a particular person to perform certain activities. The study of
the psychophysiological characteristics of these persons was performed in the
morning (from 8 to 12 a.m.) before and after rehabilitation treatment in accor-
dance with the ethical standards of the responsible committee and with the Hel-
sinki Declaration.
The study of the autonomic nervous system was carried out according to
"international standards" analysis of heart rate variability (Heart Rate Variabil-
ity, 1996) [10, 11] for five minutes in the first standard lead. The psychophysi-
ological characteristics were recorded using a special hardware and software
system "MPFY Rhythmograph 1" elaborated at the Kharkov National University
of Radioelectronics. The system is designed to monitor the heart rhythm (HR)
from the ECG signals in the first standard lead with time and spectral statistical
analysis of heart rate. The following characteristics of HRV data have been in-
vestigated in this research:
1. Statistical parameters — (mode of RR- intervals (mRR, ms), standard
deviation of RR- intervals (SDNN, ms), Baevsky stress index (IN % / s2), mode
amplitude (AMo, %);
2. Parameters of HR spectral analysis – total spectral power (TP) in the
range 0,003–0,4 Hz characterizes the overall absolute level of activity of human
regulatory systems; VLF — spectral power in the very low frequency range
0,015–0,04 Hz — relative assessment of sympathetic regulation level of activity;
LF — spectral power in the low frequency range of 0,04–0,15 Hz — relative
assessment of the vasomotor center activity; HF — spectral power in the high-
frequency range 0,15–0,4 Hz — relative assessment of the parasympathetic
regulation level of activity (respiratory waves) [0, 0, 0].
A.V. Shvets, A.Y. Kich
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The EEG study was performed using electroencephalographic complex
NeuroCom Standard developed in Scientific-technologic Center of radioelec-
tronic medical devices and technologies of National Aerospace University. The
data were recorded in 16 standard monopolar leads (Fp, F, C, T, P, O) from both
hemispheres of patients with closed eyes in accordance to the international sys-
tem "10–20" (Jasper, 1958) combined with auricular reference electrode. Sam-
pling frequency was 250 Hz. There was performed a visual and software analy-
sis for one minute EEG examination in the 1–50 Hz frequency range.
The average power of spectral data have been studied for each EEG lead us-
ing fast Fourier transformation. The value of power spectrum in standard physio-
logical frequency bands: Delta (1–4 Hz.), Theta (4–8 Hz.), Alpha (8–13 Hz.),
Beta (13–35 Hz.), Gamma (35–50 Hz.) has been analyzed. Fragments with arti-
facts were processed to their extinction based on the technology of the inde-
pendent component analysis; otherwise, they were excluded from further analy-
sis [7, 13].
Analysis of the results was performed by methods of descriptive and non-
parametric statistics (Spearman’s correlation coefficient), cluster, factor and
discriminant analyses using the STATISTICA 6.1.478.0 software [14].
RESULTS AND DISCUSSION
First of all, attention it should be paid attention to the features of the combat
traumatic brain injury. TBI has its own peculiarities, which stipulate the need for
a specific approach to the first aid, treatment and rehabilitation. At first, this is
the specific effects of damage to the anatomical integrity of the central nervous
system, which are characterized by specific violations or "exclusion" of func-
tions. Functional insufficiency is directly dependent on the level of the zone of
injury (for brain injury). The immediate consequences of violations of anatomi-
cal integrity are the violation of the regulatory, transmitter conductor, neurotro-
phic and mental functions of the human body. Neurotrauma, like most traumatic
injuries, is accompanied by a martial traumatic injury, which is often an ex-
tremely powerful complicating component in these cases.
The peculiarities of moderate and severe TBI include the significant func-
tional constraints that it leads to, in most cases, the impossibility of military du-
ties performing, the high percentage of disability, and psychosocial disadapta-
tion. The consequences of mild neurotrophy are often a violation of the psycho-
emotional sphere, which also does not contribute to the full-fledged social func-
tioning of the soldier or veteran. In addition, the possibility of specific and non-
specific complications of neurotrophy should be taken into account.
The use of high-energy weapons, mainly artillery, leads to a corresponding
increase in the number of traumatic brain damage mainly, and to a lesser extent,
injuries of the spine and spinal cord. In 2016 approximately 33,.5% were head
injuries (Fig. 1) of all combat pathology, and by mid-2017, this pathology have
been occurring almost in half of the structure of all casualties.
Thus, in the current hybrid war, damage to the central nervous system ac-
counts for more than a third of all traumas, while in recent times there has been a
tendency to increase this proportion due to the consequences of blust explosions.
The Decision Support Model for Forecasting of Wounded and Sick Restoration
ISSN 2519-2205 (Online), ISSN 0454-9910 (Print). Киб. и выч. техн. 2017. № 3 (189) 83
Fig. 1. The structure of traumatic injury in 2016.
Analysis of the EEG data shows that 45 % of patients after mTBI obtained
in wide-ranging period (3 months — 1 year) had a high level of beta activity on
the background of irregular alpha rhythm combined with diffuse delta activity.
Therefore, in our opinion, a marker for FS recovery should apply initial α / βI
EEG ratio in time of admission to hospital and α / βII before patient discharging
(after rehabilitation).
The next EEG phenomenon, which was observed in 30 % of patients, is
characterized by disorganized activity that manifests itself in slow irregular
alpha rhythm against the background of paroxysmal bursts of theta rhythm with
high amplitude. This pattern was observed among patients who get contusions of
the brain and can be explained by violation of the brain diencephalic area
(thalamic nuclei irritation). The 25 % of patients had EEG characterizing by very
low amplitude waves that can be described as a flattened version of EEG.
Furthermore, in the area of brain contusion there were local delta waves that
predominated in amplitude of delta activity in other parts of the cortex and
confirmed the right or left-side concussion (high skewness coefficient).
Statistical analysis of EEG parameters in terms of their skewness and
kurtosis indicates the presence of heterogeneity of the studied data. The
additional distribution into the more homogeneous groups was not performed
due to the small size of the studied groups; therefore, the non-parametric
methods of descriptive statistics in the next study have been used.
A history of mTBI patients is reflected on significantly lower alpha activity
in the 1st group indicating a significant activating effect of tonic brain structures,
including the pronounced influence of sympathetic autonomic nervous system.
A similar phenomenon is observed among members of the 2nd group (Table. 1).
Beta activity, which may characterize the state of working capacity of the 1 st
and 2nd groups, significantly differs from control group in average power of the
EEG spectrum in beta range. However, the average amplitude of the EEG
spectrum in beta range was significantly different fom the control group only
among the 1st group members.
A.V. Shvets, A.Y. Kich
ISSN 2519-2205 (Online), ISSN 0454-9910 (Print). Киб. и выч. техн. 2017. № 3 (189) 84
The significant difference between people of control group and patients
were observed only among members of the 1st group in the EEG theta range
indicating the presence of their pronounced neuro-emotional tension (Table 1).
The initial total average amplitude of EEG spectrum in the theta range is
significantly higher among representatives of the 1 st group comparing with the
2nd group, indicating a more pronounced neuro-emotional stress of patients with
mTBI. After rehabilitation / treatment of the 2nd group patients there was
observed a significant decreasing of the power indices in theta-band of EEG
spectrum comparing with the 1st group in which significant decrease was in the
average amplitude values of the total power range of EEG spectrum in theta-
Table 1. Average EEG spectral range data before and after rehabilitation treatment
(M ± m)
Average indices of EEG total power spectrum ranges, %
1st group 2nd group
EE
G
rh
yt
hm
Initial After
rehabilitation Initial After rehabilitation
Control group
δ 32,61±5,52## 31,38±2,79### 32,86±3,49### 24,66±1,85+###* 12,99±1,05
θ 20,12±2,83# 15,17±2,18 16,60±1,43 12,18±1,35+ 14,23±1,01
α 18,22±2,80### 19,65±3,74### 19,09±2,16### 25,60±1,84+###** 46,96±3,02
β 12,83±1,77# 11,99±0,96## 9,83±1,45### 10,93±0,93### 17,60±1,41
γ 5,53±2,47 6,04±1,60 2,21±0,76 3,10±0,85 3,21 ±0,40
α/β 1,38±0,33## 1,52±0,38## 2,23±0,36 2,53±0,33* 2,67±0,24
Average amplitude of total range EEG spectrum, mV
δ 32,20±3,08### 30,72±1,92### 30,46±3,01### 22,71±1,39+##*** 18,24±0,96
θ 21,75±2,89# 13,93±1,48+ 14,34±0,81 13,31±2,95 14,34±0,92
α 14,32±1,17### 17,57±1,84### 17,43±0,98###* 20,26±2,17## 27,21±1,22
β 13,82±1,08## 12,98±0,75## 10,77±0,54** 10,20±0,47** 10,32±0,57
γ 5,93±1,18 6,26±1,28 4,57±0,86 4,20±0,61 4,34±0,72
α/β 1,11±0,18### 1,39±0,12### 1,61±0,14###* 2,12±0,08++###*** 2,52±0,07
Average value of frequency that is dominant in each of EEG rhythms, Hz
δ 1,04±0,05### 1,43±0,10++ 1,80±0,17#*** 1,42±0,09+ 1,43 ±0,03
θ 5,65±0,14# 5,70±0,29 5,44±0,28 6,12±0,15+### 5,26 ±0,09
α 9,74±0,40 9,82±0,27 9,68±0,18 9,69±0,12 9,84± 0,10
β 15,34±0,53 14,89±0,27 14,87±0,43 15,16±0,23 15,72±0,42
γ 48,19±0,94## 47,25±2,62# 44,54±1,51* 48,81±1,04+## 39,24±2,78
Note: Statistically significant difference of EEG data between the 1 st and 2nd groups by Mann-
Whitney U-test: ***p < 0,001, **p < 0,01, *p < 0,5; #, ##, ### — statistically significant difference
of EEG data between control group and groups 1 and 2 by U-test correspond to p < 0,001, p < 0,01,
p < 0,5 levels; +, ++, +++ — statistically significant difference of EEG data before and after the
treatment by U-test correspond to p < 0,001, p < 0,01, p < 0,5 levels.
The Decision Support Model for Forecasting of Wounded and Sick Restoration
ISSN 2519-2205 (Online), ISSN 0454-9910 (Print). Киб. и выч. техн. 2017. № 3 (189) 85
band. This may indicate different mechanisms of nervous-emotional stress
overcoming at hospital level of treatment.
The EEG analysis of patients shows significant changes toward the decrease
in power of delta activity after rehabilitation / treatment of the entire cohort of
the 2nd group people, indicating a better recovery of their initial signs of central
fatigue and the effects of hypoxemia in the CNS in comparison with the 1 st
group.
Quite sensitive indicator of rehabilitation / treatment effectiveness was α / β
index. Thus, the increasing of some parts of amplitude and power of EEG
spectrum in alpha range comparing with the beta range after rehabilitation /
treatment was observed only among members of the 2nd group. Moreover, the
level of this indicator was significantly higher in the 2 nd group people compared
to the 1st group, which indicates a greater tendency to recovering normal brain
electrical activity among individuals who did not have mTBI.
Average levels of frequencies that dominate in each of EEG rhythms did not
go beyond the normative range, but have certain features. In consequence, the
average rate of EEG spectrum in the gamma range obtained from representatives
of the 1st and 2nd groups were higher than in the control group. In the time of
patients’ admission to hospital the average level of frequencies in the delta range
was significantly lower compared to the second group.
This level did not have significant difference between the control group and
both groups of patients after the treatment. Consequently, lower average
frequency at the beginning of treatment with a slight change in amplitude of
delta range indicate a slow recovery processes and signs of fatigue among
individuals of the 1st group even after the treatment. This is also confirmed by
the fact that only 23,3 % of the 1st group patients had positive changes in the
EEG data (Fig. 2).
Most people (70,0 %) of the 1st group did not have EEG changes after inpa-
tient treatment because the EEG manifestations of concussion can exist more
than three years. In some cases (6,7 %) there was recorded tendency to negative
changes in delta and alpha EEG bands, which can explained by violation of exci-
tation and inhibition in the central nervous system [0]. The betterment of the
brain electrical activity after hospital treatment was observed in most cases of 2 nd
group, (83,4 %). 13,3 % of servicemen still had essentially unchanged bioelectric
pattern and 3,3 % had its deterioration.
So, the bioelectric patterns of the 1st group of people due to excessive
stimulating effect of brain activating centers and sympathetic nervous system
characterized by significant functional deterioration of brain bioregulation and
by the growth of inhibitory processes in the central nervous system (significant,
around 7 % increase in the delta range activity). The features of recovering of
the servicemen FS in terms of the EEG data are important from theoretical and
practical point of view.
It is important for practice that against the background of a positive result of
treatment by conventional clinical indicators there were revealed the features of
FS recovering based on the EEG data, which indicate the ambiguity of the
recovery process and certain need for further rehabilitation of mTBI people. In
addition, the presence of significant inverse correlation between coefficients
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23,3
70
6,7
83,4
p<0,001
13,3
p<0,001
3,3
0
10
20
30
40
50
60
70
80
90
positive changes without changes negative changes
%
1st group 2nd group
Fig. 2. Features of FS recovery among wounded and sick patients using EEG data.
α / β (ratio of average amplitudes respectively in α and β band spectrum) before
rehabilitation treatment and the average amplitude of δ and θ ranges of the
spectrum (Spearman correlation criteria R = -0,46 and R = -0,42; p < 0,05), and
the average EEG power index in δ spectrum (R = -0,38, p < 0,05) after the
treatment demonstrate the ability to predict the degree of FS recovery (human
rehabilitation potential) based on α / β coefficient.
At its higher levels before rehabilitation / treatment in hospital conditions
there was a reduction of the δ and θ ranges contribution in the spectrum, which
may indicate a neuro-emotional stress decreasing, central fatigue signs and
effects of hypoxemia in the CNS. The level of its ratio below 1.5 may indicate
low human rehabilitation potential. In addition, according to some researches [8,
15, 16], the phenomenon of β-band dominations over the α-range indicates a
high probability of PTSD progress among military personnel.
The estimation of human adaptive capacity, and therefore the rehabilitation
potential of people can also be obtained by visual viewing of heart
rhythmography [17]. Fluctuations of heart rate and its scale can suggest a range
of regulatory process possibilities of human [18].
Considering mRR index that characterizes the energy level of functioning of
the cardiovascular system, it can be noticed that mRR index was the highest in
control group (Table 2).
Thus in patients with mTBI (Group I) mRR rate was significantly lower
than in control group. After the treatment the mRR rate was significantly
improved (p < 0,05) only in members of the 2nd group of military personnel in
comparison with the 1st group, indicating a high energy level of cardiovascular
system functioning in mTBI patients comparing with healthy individuals and
patients with therapeutic diseases.
It should be noted that most of the indexes of HRV in the 1st and 2nd groups
before discharge from the hospital were significantly different from the control
group. However, there were some features in the FS recovery of the 2nd group of
people after rehabilitation treatment. The total assessment of adaptive capacity,
which was measured in terms of SDNN, before rehabilitation treatment was the
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lowest in the 1st group. There was only a slight tendency to improving of
adaptive capacity of patients after their treatment.
The degree of centralization of heart rate’s neurovegetative regulation,
measured in terms of AMo, at the beginning of the treatment was slightly lower
in the 2nd group of people in comparison with the 1st group. The highest degree
of centralization (in terms of AMo) was observed among individuals of the 1 st
group before their discharge.
Table 2. Indexes of heart rate variability, M ± m
Before rehabilitation
Indexes of HRV
1st group 2nd group
Control group
mRR, ms 736,63±15,28### 689,71±29,99### 976,0±42,3
SDNN, ms 26,85±5,34### 35,10±4,79### 63,6±6,35
AMo, % 63,15±3,58### 56,28±4,36### 37,0±2,49
ІN, %/s2 328,03±35,15### 279,04±41,76## 150±15,22
TP, ms 2 495,67±76,16***### 976,22±67,66### 2893,15±142,14
VLF, ms 2 183,67±41,96**### 378,06±54,12### 792,18±52,14
LF, ms 2 236,33±54,42### 369,72±53,11### 1509,33±112,12
HF, ms 2 75,17±15,53*### 165,71±35,12### 593,47±42,21
LF/HF, cu 7,52±1,34*### 4,44±0,66### 1,7±0,32
VLF/HF, cu 12,68±2,40### 8,11±1,16### 1,45±0,26
(VLF+LF)/HF, cu 20,46±2,45**### 12,59±1,62### 3,11±0,42
VLF/(LF+HF), cu 0,96±0,04## 1,34±0,19## 0,58±0,11
After rehabilitation
mRR, ms 730,00±36,78### 759,91±17,56###+ 976,0±42,3
SDNN, ms 28,45±5,51### 38,40±3,50## 63,6±6,35
AMo, % 62,22±10,86# 51,21±2,92### 37,0±2,49
ІN, %/s2 317,40±67,44# 210,70±26,15# 150±15,22
TP, ms 2 619,33±82,49***### 1213,94±97,31###+ 2893,15±142,14
VLF, ms 2 279,33±54,65***### 549,90±42,00###+ 792,18±52,14
LF, ms 2 286,83±25,88***### 498,55±52,25### 1509,33±112,12
HF, ms 2 53,17±18,25***### 228,50±31,31## 593,47±42,21
LF/HF, cu 9,78±1,96**### 4,02±0,76## 1,7±0,32
VLF/HF, cu 12,52±3,07*### 4,87±0,94##+ 1,45±0,26
(VLF+LF)/HF, cu 22,14±4,48**### 8,90±1,43### 3,11±0,42
VLF/(LF+HF), cu 1,06±0,32 1,08±0,18# 0,58±0,11
Note: Statistically significant difference of HRV data between 1st and 2nd groups by Mann-Whitney
U-test:***p < 0,001, **p < 0,01, *p < 0,5; #, ##, ### — statistically significant difference of HRV
data between control group and groups 1 and 2 by U-test correspond to p < 0,001, p < 0,01, p < 0,5
levels; +, ++, +++ — statistically significant difference of HRV data before and after the treatment
by U-test correspond to p < 0,001, p < 0,01, p < 0,5 levels.
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It is noteworthy that most of the spectral characteristics of HRV (TP, VLF,
LF, HF, LF / HF, VLF / HF, (VLF + LF) / HF) were significantly better in the
members of the 2nd group in comparison with the 1st group before and after the
rehabilitation treatment in hospital conditions.
The index of vegetative balance (LF / HF) obtained from the 1 st group of
people had the highest level comparing with other groups, indicating a marked
tension of regulatory processes due to mostly sympathetic nervous system
influence on patients with mTBI in history.
The index of subcortical nerve centers activation (VLF/HF) before the
treatment was the highest in the 1st group of people. Before discharge patients
the VLF/HF rates significantly differs only in members of the 2 nd group.
The index of centralization ((VLF + LF) / HF) is the highest in the first
group of people that indicates the presence of disadaptation processes in patients
with mTBI and violation of regulation at both segmental (basal) and
suprasegmental (nuclear) brain structures, and reducing of inhibitive cerebral
cortex influence on them. The centralization index was not significantly changed
after the treatment in all studied groups, but the tendency to it improvement was
observed in members of the second group.
The subcortical-stem index (VLF / (LF + HF) was not significantly
transformed after the treatment in the 1 st and 2nd groups of people and mostly
was characterized by predominance of the central influence on the heart rhythm
control, reflecting the tension of the system functioning and the trend to double
control of regulation processes.
It should be noted that the low level of modulation of hormonal regulatory
mechanisms according to typical indicator VLF was observed in the 1 st and 2nd
groups before admission to the hospital. The significant improvement (p < 0,05)
of regulatory processes was only occurred among the members of the 2 nd group
after their treatment. However, the low levels of mobilization and rehabilitation
potentials of human that were measured in terms of HF and LF indexes at the
beginning of rehabilitation treatment in hospital conditions become moderate in
average range 300–700 ms2 after the treatment of the 2nd group members.
The total power of neurohumoral regulation spectrum was very low in the
1st and 2nd groups comparing with normative values. This indicates the presence
of fatigue, which is accompanied by decreasing of human creative potential and
performance. The time and resources needed for human recovering are signifi-
cantly higher in patients of studied groups. The hypoergic variants of response
are inherent to most representatives (70 %). Only 13 ,3 % of people have TP in-
dexes within the physiological norm.
Positive is that the TP is significantly improved in the representatives of the
2nd group after rehabilitation treatment, indicating a better adaptation reserve of
them comparing with persons of the 1st group. Thus, we can conclude that peo-
ple with adaptation disorders (1st and 2nd groups) were characterized by a high
level of centralization of regulation of the cardio circulation system in terms of
HRV data before the treatment, which reflects in some cases a higher physio-
logical regulation value of FS.
It has been found that only 30% of the 1st group members had positive
changes in HRV data (Fig. 3).
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Most people (63,3 %) of the 1st group did not have changes in the HRV
characteristics after a treatment in hospital. In some cases (6 ,7 %) a tendency to
adverse changes in spectral HRV characteristics has been recorded. The
betterment of HRV characteristics after hospital treatment of the second group
representatives have been improved in most cases (70 %). 23 ,3 % of people had
HRV parameters which are essentially remained unchanged. The deterioration of
HRV parameters in 6,7 % cases has been observed too. The last case was also
described in similar studies of other scientists and corresponds with their data
[15, 19].
An important step in this research was to find interconnections for establish-
ing the degree of tension of regulatory processes. This has been done by using a
cluster analysis (clustering criterion was 1 — Spearman R).
As a result, the correlation between HRV and EEG parameters before the
treatment of the 1st group patients were stronger indicating a fairly inflexible
structure of regulatory processes of patients with mTBI. (Fig. 4A). It is
confirmed by existence of strong correlation between EEG statistical parameters
and HRV spectral characteristics (mRR, SDNN, TP, VLF, LF, HF). In addition
to this, the stress index of HRV is strictly related with AMo and other HRV
frequency characteristics.
After the rehabilitation treatment the interconnections structure has been
changed. The statistical and spectral characteristics of HRV (mRR, SDNN, TP,
VLF, LF, HF) correspond only with such EEG indices that characterize the brain
activity in alpha and beta-band spectrum only.
The HRV stress index is associated with the brain electrical activity in the
theta range. The correlation between average amplitude of EEG spectrum in
gamma and delta bands with HRV indices become less obvious (only with the
delta range data). This indicates some reduction in tension of regulatory
processes in human organism.
Another depiction of interactions is observed among members of the second
group. The fig. 5 shows that the characteristics of EEG in delta and theta bands
are associated with indices of HRV spectral characteristics (LF / HF, VLF / HF,
VLF / (LF + HF), (VLF + LF) / HF). The EEG indicators in alpha and beta
bands have less correspondence with these characteristics.
The correlations strength between EEG and HRV parameters was decreased
after the treatment of the ATO participants who had therapeutic pathology
(R < 0,4). Thus, the members of the 2nd group after the rehabilitation treatment
can be characterized by decreased tension of regulatory processes, as evidenced
by a decreasing of intersystem relations strength. To predict the human
rehabilitation potential it was used the shifts of normalized characteristics of
EEG and HRV data (differences before and after treatment, taking into account
the direction of change, to average group parameters obtained from every person
before the treatment in hospital). As a result of this procedure the normalized
levels of EEG and HRV indices shifts that have both positive and negative
changes have been derived.
A.V. Shvets, A.Y. Kich
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30,0
63,3
6,7
70, 0
p<0,001
23,3,
p<0,001
6,7
0
10
20
30
40
50
60
70
80
positive changes without changes negative changes
%
1st group 2nd group
Fig.3 2. Features of FS recovery of wounded and sick based on HRV data.
LF
/H
F
V
LF
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(V
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s2
m
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m
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m
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m
s m
s s2
m
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m
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m
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m
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s m
s
A B
Fig.4 3. Cluster structure of intersystem interactions between EEG and HRV data before
(A) and after (B) rehabilitation treatment of mTBI patients.
V
LF
, м
с^
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, м
с^
2
H
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B
et
a
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et
a
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(V
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/H
F
V
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V
LF
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Th
et
a
D
el
ta
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et
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ta
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H
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(V
LF
+L
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F
V
LF
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F
LF
/H
F
IН
, %
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A
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o,
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G
am
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a
V
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, м
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, м
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, м
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R
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cu cu
m
s
m
s
m
s2
m
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m
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m
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m
s2
А B
Fig. 5. Cluster structure of intersystem relationships between EEG and HRV data before
(A) and after (B) rehabilitation treatment of therapeutic patients.
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It was used the factor analysis of these shifts for integration of the obtained
normalized characteristics. As a result of this analysis, two factors have been
allocated. The first one (F1) consists of parameters which mostly characterize
the energy level of regulation of the human body in terms of HRV spectral
characteristics (contribution of this factor to the overall dispersion is 37 %) and
F2, which mostly consists of EEG indices (the contribution of this factor in the
total dispersion is 23 %). The factor values, which demonstrate the effectiveness
of the human FS recovery, have been obtained for each of these factors. If the F1
and F2 ≥ 0 the recovery of a patient FS is positive, otherwise the FS recovery
can be seen as negative.
It was used the multiple step-up regression analysis for prediction of human
rehabilitation potential (at any stage, rather than entering all the variables as a
block, step-up regression enters the variables one at a time, the order of entry
determined by the variable that causes the greatest R2 increase, given the
variables already entered into the model) where the characteristics of HRV and
EEG data before the treatment of a patient were independent variables and factor
values for F1 and F2 were dependent variables.
Only one decision support model for human rehabilitation potential has
been built (R = 0,86, p < 0,001) as a result of this analysis:
F1 = 0,17 + 0,0004*ТР - 0,07*β - 0,02*VLF/HF,
where TP — the total power of HRV spectral density (characterizes the overall
absolute level of activity of regulatory systems, ms 2); β — average amplitude of
EEG spectrum in beta-band mV; VLF / HF — index of activation of subcortical
nerve centers, cu.
The following criteria for referring people to the group with "high /
satisfactory" rehabilitation potential are:
• F1≥0 — patient has a "high / satisfactory" rehabilitation potential (FS
recovery is positive);
• F1 <0 — patient has "low" rehabilitation potential (FS of human is
recovering slowly or not recovering at all).
The selection of individuals with “low” rehabilitation potential is important
because they need continuing treatment in rehabilitation centers, despite the
positive changes in generally accepted clinical symptoms. Furthermore, a doctor
should focus on the HRV data besides the other health indicators when he or she
makes a decision about the degree of human FS recovery as well as the
effectiveness of physical therapy or spa treatments, physical exercises. When
HRV is higher the pronounced symptoms of autonomic dysfunction is less and
can be conducted with more intensive rehabilitation process.
Hence, adaptation and rehabilitation opportunities of the human organism
are easier to quantify using HRV parameters based on spectral analysis: TP,
LF/HF, HF, LF, and VLF. When the total power spectrum is higher, the human
FS is better and higher its rehabilitation potential. However, it should be kept in
mind, how the way of the FS supporting mechanisms are going on (indicators
VLF / HF or HF, LF, VLF).
In terms of the optimal physiological mechanism of the FS supporting is
regulation by emergency response system — HF component. On the other hand,
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excessive activation of one of the regulation systems is inevitable and like any
unilateral process leads to its imbalance and therefore requires adequate
involvement of others components in the regulatory process. This one is
reflected in the appearance of low waves (LF) and very low (VLF) waves in
HRV frequencies, which shows the impact of sympathetic, and humoral-
metabolic (cerebral ergotropic) modulation effects on heart rate. The extremely
low possibility of rehabilitation could be confirmed when the total power
indicator (TP) is less than 200 ms2 and there is an imbalance in autonomic
nervous system, and in spectral power structure a very slow regulation
component (VLF) is dominated. Therefore, examination of the HRV and EEG
characteristics in clinical medicine can help to evaluate the current functional
state and the rehabilitation potential of human.
If concomitant diseases of the cardiovascular system (hypertension,
ischemic heart disease, arrhythmias) exist, the HRV examination should be
separated because it can’t asses the level of FS recovery comparing with other
pathologies. However, this study provides the opportunity to stratification of
patients at complication risks, in other words, to identify a group of patients who
is going to have a high risk of complications during physical therapy, fitness and
spa procedures, and select a group of patients whom such procedures are not
contraindicated. Therefore, the study of HRV in cardiac patients with prognostic
aim remains a screening method with high sensitivity but low specificity.
The levels of energy (HRV) and information-energy (EEG) components of
providing working capacity indicate the presence of different mechanisms for
harmonization physiological processes that occur in the first and second groups
of people. The detailed interpretation of these additional effect needs in-depth
analysis of studied material, because the age aspect and somatic pathology
details as well as other functional characteristics (stabilography, psychomotor
reaction, predominance of the brain default-mode network, etc.) have been not
took into account in this study.
CONCLUSIONS
The “price” of the functional state regulation among wounded and sick people
assessed by HRV and EEG characteristics is the highest in individuals with
mTBI on different levels of physiological functioning. These patients have a
significant tension of physiological processes in the body; while patients with
other disorders have significantly better functional state recovering as well as
decreasing of protective inhibition in the central nervous system after rehabilita-
tion in hospital conditions.
The decision support model regarding assessment of medical recovery by
evaluation of functional state of wounded and sick persons allows quantitatively
predict the need for further rehabilitation after the hospital treatment which is
necessary to unify of rehabilitation approaches in different levels of health care
of patients to maintain rehabilitation continuity and steadiness.
Application of EEG and HRV hardware during rehabilitation of combatants
in hospital conditions allows to evaluate a specific morphological defects and the
degree of human rehabilitation potential, to predict the likelihood of
inappropriate and / or paradoxical reactions on the therapeutic treatment, to form
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an advice to therapeutic optimization of the rehabilitation taking into account a
background of neurohumoral regulation. The important role of military
psychophysiologists and significance of their integration to the rehabilitation
process at hospital level for comprehensive diagnosis and proper treatment of
patient with mTBI is growing up nowadays.
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Posttraumatic Stress Disorder in Active-Duty Marines. JAMA Psychiatry. 2015. 10 (2).
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Received 12.06.2017
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The Decision Support Model for Forecasting of Wounded and Sick Restoration
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Получено 12.06.2017
А.В. Швец1, д-р мед. наук, старш. науч. сотр.
Начальник научно-исследовательского отдела специальной медицины и психофизио-
логии НИИ проблем военной медицины Украинской военно-медицинской академии
e-mail: shvetsandro@gmail.com
А.Ю. Ких2, канд. мед. наук,
начальник Военно-медицинского клинического центра профессиональной патологии
военнослужащих Вооруженных Сил Украины
e-mail: kikh76@ukr.net
1 НИИ проблем военной медицины Украинской военно-медицинской академии, ул. Мельнико-
ва, 24, г. Киев, 04655, Украина.
2 Военно-медицинский клинический центр профессиональной патологии военнослужащих
Вооруженных Сил Украины, ул. 11-я линия, 1, г. Ирпень, Киевская область, 108203, Украина
МОДЕЛЬ ПОДДЕРЖКИ ПРИНЯТИЯ РЕШЕНИЯ ДЛЯ ПРОГНОЗИРОВАНИЯ
СТЕПЕНИ ВОССТАНОВЛЕНИЯ ВОЕННОСЛУЖАЩИХ В ГОСПИТАЛЬНЫХ
УСЛОВИЯХ НА ОСНОВЕ ПСИХОФИЗИОЛОГИЧЕСКИХ ДАННЫХ
Выявлены особенности восстановления характеристик ВСР и ЭЭГ, которые заключа-
ются в существенно худшем восстановлении функционального состояния (ФС) группы
военнослужащих с контузией головного мозга по сравнению с лицами, которые не
имели контузии мозга в анамнезе (соответственно 23,3% и 83, 4% лиц с положитель-
ной динамикой, p <0,001). Описаны структурные особенности 3-х ЭЭГ-феноменов,
которые встречаются у лиц с контузией головного мозга. Анализ межсистемных связей
ЭЭГ и ВСР дополнительно свидетельствует о медленном восстановлении ФС у лиц I
группы. С помощью факторного анализа нормированных характеристик изменения
показателей ЭЭГ и ВСР до и после восстановительного лечения построена регрессион-
ная модель поддержки принятия решения с целью прогнозирования реабилитационно-
го потенциала человека и эффективности реабилитации в госпитальных условиях.
Ключевые слова: реабилитационный потенциал, участники антитеррористической
операции, функциональное состояние, вариабельность сердечного ритма, электроэн-
цефалография.
A.V. Shvets, A.Y. Kich
ISSN 2519-2205 (Online), ISSN 0454-9910 (Print). Киб. и выч. техн. 2017. № 3 (189) 96
А.В. Швець1, д-р мед. наук, старш. наук. співроб.
Начальник науково-дослідного відділу спеціальної медицини та психофізіології НДІ
проблем військової медицини Української військово-медичної академії
e-mail: shvetsandro@gmail.com
А.Ю. Кіх 2, канд. мед. наук,
начальник Військово-медичного клінічного центру професійної патології
військовослужбовців Збройних Сил України
e-mail: kikh76@ukr.net
1 НДІ проблем військової медицини Української військово-медичної академії, вул. Мель-
никова, 24, м. Київ, 04655, Україна
2 Військово-медичний клінічний центр професійної патології військовослужбовців Збройних
Сил України, вул. 11-а лінія, 1, м. Ірпінь, Київська область, 108203, Україна
МОДЕЛЬ ПІДТРИМКИ ПРИЙНЯТТЯ РІШЕННЯ ЩОДО ПРОГНОЗУВАННЯ
СТУПЕНЯ ВІДНОВЛЕННЯ ВІЙСЬКОВОСЛУЖБОВЦІВ
У ГОСПІТАЛЬНИХ УМОВАХ НА ОСНОВІ ПСИХОФІЗІОЛОГІЧНИХ ДАНИХ
Виявлені особливості відновлення характеристик ВСР і ЕЕГ полягають в істотно гір-
шому відновленні функціонального стану (ФС) групи військовослужбовців з контузією
головного мозку в порівнянні з особами, які не мали контузії мозку в анамнезі (відпо-
відно 23,3% та 83, 4% осіб з позитивною динамікою, p < 0,001). Описано структурні
особливості 3-х ЕЕГ-феноменів, які зустрічаються у осіб з контузією головного мозку.
Аналіз міжсистемних зв'язків ЕЕГ і ВСР додатково свідчить про повільне відновлення
ФС у осіб I групи. За допомогою факторного аналізу нормованих характеристик зміни
показників ЕЕГ і ВСР до і після відновного лікування побудована регресійна модель
підтримки прийняття рішення з метою прогнозування реабілітаційного потенціалу
людини і ефективності реабілітації в госпітальних умовах.
Ключові слова: реабілітаційний потенціал, учасники антитерористичної операції,
функціональний стан, варіабельність серцевого ритму, електроенцефалографія
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