Šiame darbe, remiantis biofizikiniais modeliais bei daugiamatės analizės metodais, buvo kuriami elektrokardiosignalų analizės metodai, leidžiantys:
a) įvertinti autonominės širdies veiklos reguliavimo efektyvumą pasy-vios bei aktypasy-vios ortostazės mėginio metu;
b) įvertinti centrinę hemodinamiką;
c) perspėti apie galimą staigią kardialinę mirtį. Buvo nagrinėjami šie signalai:
a) 12 derivacijų elektrokardiogramos P bangos, registruotos aktyvios ortostazės mėginio metu;
b) DI derivacijos elektrokardiogramos P bangos, registruotos pasyvios ortostazės mėginio, atlikto Mikrogravitacijos tyrimo centre, Porto Alegre, Brazilijoje, metu;
c) elektrokardiogramos T bangos kaitą kas antrame širdies dūžyje at-spindintys signalai buvo gauti iš PhysioNet/Computers in
Cardio-logy Challenges duomenų bazės (http://physionet.org/pn3/twadb/), kurioje buvo ekspertų atrinkti klinikiniai įrašai, bei biofizikinio trimačio širdies elektrinės veiklos dinaminis modelio, pagrįsto šir-dies vieno dipolio modeliu bei trimate vektorkardiograma, generuo-ti signalai;
d) krūtinės ląstos impedansas bei pulso bangos signalas, registruo-jamas galūnėse;
e) KMUK kardiologijos intensyvios terapijos skyriuje kaupiami 24 val. stebimų ligonių ūmioje miokardo infarkto stadijoje EKG įrašai. Minėtų signalų analizei naudoti metodai:
a) elektrokardiosignalų struktūrinė analizė; b) pagrindinių komponentų analizės metodas; c) duomenų klasterizavimo algoritmas KLASTAN. d) nepriklausomų komponenčių metodas;
P bangos morfologijos pokyčių pasyvios bei aktyvios ortostazės sąlygo-mis vertinimas bei T bangos kaitos kas antrame širdies dūžyje radimas iliustruoja iš esmės to paties tipo uždavinio sprendimą: užregistruoti signalai yra įvairių tuo pačiu metu vykstančių reiškinių mišinys, o atliekamos ana-lizės tikslas yra vieno ar kelių konkrečių to mišinio komponenčių išskyrimas bei įvertinimas.
Darbo metu pastebėjome, kad pradinis duomenų paruošimas (pvz., EKG struktūrinė analizė) yra vienas esminių visos analizės žingsnių. Šio etapo rezultatai stipriai įtakoja galutinius taikomų metodų rezultatus. Pavyzdžiui, pastebėjome, kad mūsų sukurtiems metodams absoliučiai kritiškas yra,
tarkim, kvaziperiodinio signalo atpažinimas laike. Jei varijuoja, pvz., EKG kardiociklo atpažinimas, šio elektrokardiosignalo analizė toliau tampa ne-efektyvia.
Darbo metu sukurti kiekybiniai elektrokardiosignalų, atspindinčių širdies veiklos reguliavimą, centrinę hemodinamiką bei T bangos kaitą kas antrame širdies dūžyje, morfologijos vertinimo metodai atveria naujas informacinių technologijų panaudojimo galimybes e-sveikatos klinikinių sprendimų pa-laikymo sistemoje, didinant diagnostikos efektyvumą bei gerinant kliniki-nius sprendimus.
Darbas, atliktas kuriant autonominio širdies veiklos reguliavimo efekty-vumo vertinimo metodą pasyvios ortostazės mėginio metu ir kintančios gra-vitacijos sąlygomis, yra kolektyvinio (Kauno medicinos universiteto ir Brazilijos Porto Alegre Mikrogravitacijos tyrimo centro mokslininkų) darbo rezultatas, pasiektas pasitelkus naujausias informacines technologijas, ro-dantis virtualus bendradarbiavimo galimybes ne tik tarp nutolusių institucijų bet ir biomedicininės diagnostinės informacijos gavimo ir apdorojimo ga-limybes sunkiai prieinamose vietose.
IŠVADOS
1. Biofizikiniai modeliai atskleidžia širdies veiklą atspindinčių signalų sandarą ir leidžia tinkamai sukurti signalų pirminio apdorojimo todus, didele dalimi lemiančius sėkmingą daugiamatės analizės me-todų taikymą.
2. Pagrindinių komponenčių analizės metodas sukuria optimalius širdies elektrinės veiklos bei kraujotakos pokyčių, kurie pertekliškai bet visa-pusiškai atsispindi signalų morfologijoje, įverčius.
3. Nepriklausomų komponenčių analizės metodas leidžia išskirti krūtinės ląstos impedanso signalo įverčius, detaliai atspindinčius centrinę krau-jotaką.
4. Daugiamatės analizės būdu išskirti širdies veiklos bei kraujotakos įver-čiai yra ne tik naudingi diagnostikai, bet ir atskleidžiant naujas širdies ir kraujotakos sistemos funkcionavimo ypatybes.
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