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Врачи и преподаватели должны быть осведомлены о наличии и выраженности нарушений сна у наблюдаемых студентов и активно помогать им понять важность сна для сохранения не только высоких показателей успеваемости, но и физического и психологического здоровья. Сами же студенты должны учитывать тот факт, что нарушения сна могут являться маркером серьезных заболеваний и стараться предотвратить их.
Список литературы/References
1. Лышова О.В. Скрининговое исследование нарушений сна, дневной сонливости и синдрома апноэ во сне у студентов первого курса медицинского вуза / О.В. Лышова, В.Р. Лышов, А.Н. Пашков // Медицинские новости, 2012. № 3. С. 77-80.
2. Латышевская Н.И. Гендерные различия в состоянии здоровья и качестве жизни студентов / Н.И. Латышевская, С.В. Клаучек, Н.П. Москаленко // Гигиена и санитария, 2004. № 1. С. 51-54.
FRAGMENTARY IMITATING MODELING OF RADIAL ARTERY'S
PULSE SIGNAL
Simonyan E.E. (Russian Federation) Email: Simonyan330@scientifictext.ru
Simonyan Elena Ernstovna - Student, FACULTY OF GENERAL MEDICINE, NORTHERN STATE MEDICAL UNIVERSITY, ARKHANGELSK
Abstract: this article describes the path offragmentary simulation of the pulse signal from the radial artery. The radial artery pulse has long been one of the major diagnostic methods in both Eastern and Western medicine. Two thousand years ago, the Greek medical scientist Galen classified pulse waves and used them for clinical diagnoses, and his diagnosis theory remained in use until the medieval era .It is proposed to distinguish two archetypes of pulse signals, which allows a more selective approach to the structure of the simulation model. The concept of a universal modeling function is introduced, which introduces uniformity in the synthesis of signal models. Keywords: pulse signal, an archetype, amplitude-time characteristics, the modeling function.
ФРАГМЕНТАРНОЕ МОДЕЛИРОВАНИЕ ИМПУЛЬСНОГО СИГНАЛА
ОТ ЛУЧЕВОЙ АРТЕРИИ Симонян Е.Э. (Российская Федерация)
Симонян Елена Эрнстовна - студент, лечебный факультет, Северный государственный медицинский университет, г. Архангельск
Аннотация: в данной статье анализируется имитационный фрагментарный пульсовой сигнал от лучевой артерии. Выделяется всего два вида пульсовых сигналов, вследсвие чего имитационная модель создается крайне избирательно. Импульс радиальной артерии уже давно является одним из основных диагностических методов как в восточной, так и в западной медицине. Две тысячи лет назад греческий медицинский ученый Гален классифицировал пульсовые волны и использовал их для клинических диагнозов, и его теория постановки диагноза оставалась в употреблении до средневековья.
Ключевые слова: импульс сигнала, амплитудно-временные характеристики, функция моделирования.
The use of pulse signals of the radial artery in the problems of medical diagnostics presupposes the formalization of pulse signals, including by creating their models. For the practical implementation of simulation of signals, we define their two archetypes, in the sense of the original basic samples, the differences from which in specific pulse signals are caused by the physiological characteristics of the organism. In this case, the property of polyattraction is manifested [4] - one part of the signals correlates better with the first archetype, and the other part, respectively with the second one. The first archetype is called the S-archetype (archetype S) - from the English. Susceptible, and the second - archetype V - from eng. (viscous).
In Fig. 1 shows the signals characteristic of each of the archetypes. A is the amplitude of the signal, and t is the time. Formally, the translation of the form from one archetype to another can be done by applying the integration operation to the S-archetype, and the operations of differentiation to the V-archetype, which is illustrated by the dashed line in Fig. 1b.
Then the case of the S-archetype is considered. Visually, the shape of one period of the S-archetype signal looks like a typical damped forced oscillation caused by impulse action (in this case, a portion of the blood entering the radial artery into the wrist area), which was used earlier for modeling the pulse signal [3]. At the same time, various factors influence the shape of the detected signal: the pulse sensor features, physical loads, emotional state, physiological characteristics of the organism, including the elasticity of blood vessels, depending to a large extent on age, etc. [1].
Also, the shape of the signal can have differently expressed features associated with local processes occurring in the radial artery in the region of signal removal [2]. In Fig. 2 shows one period of the signal of the S-archetype with a sufficiently pronounced effect of distortion of the form of the damped oscillatory process.
A
A
Fig. 1. S-archetype (a) and V-archetype (b) of pulse signals
M
Fig. 2. Illustration of "symptomatic" arcs d1, d2 and d3
Perhaps this is a manifestation of the effect of reflection of the wave from the range of bifurcations. Under the area of bifurcations we mean the hierarchy of branching of the radial artery, which are successively and tree-like beyond the point of removal of the pulse, and the most noticeable effect is produced by the first branch. To emphasize the manifested local features, the figure shows the "symptomatic arcs" of arc d1, d2 and d3, approximating and emphasizing these local features, AS is the amplitude of the "systolic" tooth, tS is the time of its appearance, AF is the amplitude of the "dicrotic" The time of its appearance.
We introduce the concept of a universal modeling authigenic function (UMAF) fu (t), which has a dual character - on the one hand, the functional dependence can reflect the influence of various factors, on the other, it is authigenic, ie, its application is valid for modeling in a certain localized time interval: fa(i) = au(t-rn) h(t-rn) Sin(2n mu du(t-m)+yu) (1+h(t-xb) (Au(t-xb)-1))+cu, where: au is the amplitude modulation function realizing the damping effect of the forced oscillation caused by the impulse action; H is the Heaviside function; Bu - the multiplicative component for additional mixing (suppression) of the signal - reflects the effect of the total counteraction of various intrasystem factors to the appearance of an external effect, realized after the amplitude of the forced oscillation decreases to some comparable level (with a potential level of counteraction force) during its decay (hypothetical manifestation of the "local" Homeostasis); Cu is the additive component caused by a non-zero mean value of the signal; Du is the time distortion function, which reflects the violation of the periodicity of the oscillatory process due to the nonlinearity of the system; Mu - scaling time constant, which determines the initial frequency of the modeling oscillation; Фu is the initial phase of the modeling oscillation; Tu - initial time point of action of the UMAF; Tb is the initial time point of the bu action.
An expanded expression of the pulse simulation simulation function:
fp(t) = ag(t-Tg)hg(t-Tg) Sin(2nmgdg(t-Tg)+фg)+ar(t-vr)hr(t-vr) Sin(2nmrdr(t-rr)+|r)+ aw(t-vw)hw(t-zw) Sin(2nm wdw(t-Tw)+|w). Where: 9g = n / 2, фг = 0, фЬ = 0; Tg is the moment of the systolic maximum of the selected signal period (ts in Fig. 2); Ag (t = Tg) = As, the inertia interval for this component is not more than (a quarter of the duration of the first period of the forced oscillation); Ar (t = Tr) = (0,1 ... 0,2) As, the inertia interval is less than Q4.
For simplicity, the multiplicative and additive components are removed. The magnitude of the time scale constant mg is determined based on the initial frequency of the modeling oscillation in the range 3.5 ... 5 Hz. The scale constant mr is determined starting from the initial hypothetical frequency of the reflected wave, which is more than 6-7 Hz. In this case, the distance from Tg to Tr is slightly more than Q4. We note an essential difference in the frequencies of the damped oscillation and the reflected wave, which is explained not only by the nonlinearity of the system, but also by the special character of the formation of the reflected wave.
We note that, in contrast to the theoretical impulse action, the pulse of the portion of blood entering the pulse removal region is stretched in time, and also that the observed process is not a damped oscillation in the classical form, but only simulated as such.
References / Список литературы
1. Boronoev V. V. Analysis of pulse wave in an automated mode // Biomedical Engineering, 2014. № 4. P. 33-36.
2. Ilyukhin O.V., Lopatin Y.M. pulse wave velocity and elastic properties of the main arteries VolGMU // Bulletin, 2006. № 1. P. 3-8.
3. Guchuk V.V. Technology objectification peer clustering weakly formalized objects / Bulletin USATU, 2014. T. 18. № 5. Р. 149-154.
4. Wouter Huberts, Koen Van Canneyt Ugent, Patrick Segers Ugent. Experimental validation of a pulse wave propagation model for predicting hemodynamics after vascular access surgery // Journal of Biomechanics, 2012. № 45 (9). P. 1684-1691.
