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Instrumental gait analysis in the ACL patient
Lalaeva, Anna ; Dudová, Agnieszka (advisor) ; Lopot, František (referee)
Title: Instrumental Gait Analysis in the ACL Patient Aim: to present an up to date review on the topic of instrumental analysis of straight ahead gait on a plain surface (both over-ground and on a treadmill) in ACL patients (both deficient and reconstructed). A second aim is to introduce the clinician (especially in the field of physiotherapy/rehabilitation) to the topic of gait analysis and its specific use for the ACL patient. Methods: a systematic review on the topic Results The review answers the questions of what instrumentation, phases of gait and variables is best to use/measure for clinical purposes. It also identifies and discusses three main gait strategies used by ACL patients: quadriceps avoidance, knee stiffening, pivot shift avoidance. Keywords: gait, analysis, walking, clinical, instrumental, anterior cruciate ligament, ACL, deficient, reconstruction, injury
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Multiple sclerosis detection
Kopuletý, Michal ; Mangová, Marie (referee) ; Uher, Václav (advisor)
This thesis is focused on detecting multiple sclerosis lesions from magnetic resonance images. Correctly retrieved lesions are very important for medical diagnosis. Detection of lesions using machine learning techniques is quite challenging because of large variability in size, shape and position of lesions in the brain. In the practical part is designed base software, which after completion will classify pixels, so that is possible to find lesions of multiple sclerosis. For classification will be used Support vector machine. Theoretical part describes multiple sclerosis, basic operations performed with biomedical images and data classification.
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