| Title |
Kompleksinės elektroninės sistemos, skirtos žmogaus absoliutinio intrakranijinio slėgio neinvaziniam matavimui, tyrimai / |
| Translation of Title |
Investigation of the complex electronic system dedicated for the human non-invasive absolute intracranial pressure measurement. |
| Authors |
Bartušis, Laimonas |
| Full Text |
|
| Pages |
119 |
| Keywords [eng] |
non-invasive measurement ; intracranial pressure ; automated positioning subsystem |
| Abstract [eng] |
Intracranial pressure (ICP) is a cerebrospinal fluid pressure inside the skull or spinal canal. Absolute ICP can only be measured by using the invasive methods in worldwide clinical practice. The scientific-technological problem that is solved in this work is as follows: in which way it is possible to measure the non-invasively and without the assistance of a highly qualified specialist the absolute value of ICP with the accuracy, precision and duration required for the clinical practice? The work hypothesis follows from the formulation of the problem: it is possible to measure the absolute value of ICP non-invasively and without the assistance of a highly qualified specialist with accuracy, precision and duration required for the clinical practice by using the patented non-invasive ICP measurement method proposed by prof. A. Ragauskas and automating location of the intracranial (IOA) and extracranial (EOA) segments of the ophthalmic artery (OA) required for the ICP measurement. The work hypothesis is proved by means of the statistically reliable non-invasive ICP measurements of neurologic, severe traumatic brain injured, glaucoma patients and healthy volunteers. The location algorithm of internal carotid artery and IOA and EOA segments of the OA was created and revealed in this work, which automatically controls the spatial position and orientation of ultrasonic transducer on the closed eyelid. Depths of IOA and EOA segments needed for the ICP measurement and the duration of the segments location were determined experimentally by using the developed location algorithm. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Doctoral thesis |
| Language |
Lithuanian |
| Publication date |
2015 |
