By measuring cerebral blood volume (CBV) and intracranial pressure (ICP) variations at the same running time during sleep, it has been demonstrated that the ICP wave which appears during the REM sleep in hydrocephalic...
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By measuring cerebral blood volume (CBV) and intracranial pressure (ICP) variations at the same running time during sleep, it has been demonstrated that the ICP wave which appears during the REM sleep in hydrocephalic infants is produced by intracerebral vaso-dilatation. Nine infants with stabilized hydrocephalus were investigated by non-invasive means: REM phases were distinguished with the usual polysomnographic electrodes. Intracranial pressure was measured with a fontanel palpation transducer and CBV variations were obtained by recording 99mTc activity at the head level after in vivo labelling or red cells with 99mTc — pertechnetate. The timeactivity curves, obtained from regions of interest and selected on the sequential radioisotope images, show that an increased ICP wave, occurring during the REM period, is related to a simultaneous increase in the blood volume, limited to the cerebral sector and not to the area of the external carotid artery.
The ability of a robot to navigate itself in the environment is a crucial step towards its autonomy. Navigation as a subtask of the development of autonomous robots is the subject of this thesis, focusing on the devel...
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The ability of a robot to navigate itself in the environment is a crucial step towards its autonomy. Navigation as a subtask of the development of autonomous robots is the subject of this thesis, focusing on the development of a method for simultaneous localization an mapping (SLAM) of mobile robots in six degrees of freedom (DOF). As a part of this research, a platform for 3D range data acquisition based on a continuously inclined laser rangefinder was developed. This platform is presented, evaluating the measurements and also presenting the robotic equipment on which the platform can be fitted. The localization and mapping task is equal to the registration of multiple 3D images into a common frame of reference. For this purpose, a method based on the iterativeclosestpoint (ICP) algorithm was developed. First, the originally implemented SLAM method is presented, focusing on the time-wise performance and the registration quality issues introduced by the implemented algorithms. In order to accelerate and improve the quality of the time-demanding 6DOF image registration, an extended method was developed. The major extension is the introduction of a factorized registration, extracting 2D representations of vertical objects called leveled maps from the 3D point sets, ensuring these representations are 3DOF invariant. The extracted representations are registered in 3DOF using ICP algorithm, allowing pre-alignment of the 3D data for the subsequent robust 6DOF ICP based registration. The extended method is presented, showing all important modifications to the original method. The developed registration method was evaluated using real 3D data acquired in different indoor environments, examining the benefits of the factorization and other extensions as well as the performance of the original ICP based method. The factorization gives promising results compared to a single phase 6DOF registration in vertically structured environments. Also, the disadvantages of the method ar
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