The life expectancy of the elderly population is expected to increase with 22 % by 2050. As one grows older, the body starts to deteriorate, which can lead to a higher risk for diseases and accidents. During recent years shoulder surgeries have increased dramatically, and to assess the shoulder function the most common technique is the use of camera-based motion capture systems. However, this is very time consuming and does not completely represent the real shoulder performance. Therefore, this study was aimed to validate a new technique, the force range monitor (FRM). Thirteen volunteers participated in this study, which was divided into two sessions. Session one included abduction and flexion strength measurements using the FRM, as well as six mobility measurements with the inertial measurement unit (IMU) of the FRM. The second session was conducted in the same manner, with the addition of the Vicon system (motion capture system). In this study a control session for FRM and the Vicon system was also performed for abduction and flexion movements with two participants, where the placement of the IMU was modified. As indicated by the results, FRM and the Vicon system do not measure the same parameters. Even if the FRM does not measure the same shoulder joint angles as the Vicon System, the FRM can still be of clinical importance when evaluating position deviation during strength and mobility measurements. Moreover, the FRM had a high repeatability for a number of participants, and most of the mobility measurements presented a distinct patterns for various activities. Hence, it can be concluded that the FRM is a potential technique to evaluate shoulder strength and mobility.

The aim of the thesis is a realization of advanced analysis of signals from gait laboratory. The introductory part deals with the gait cycle and its relation to the joints kinematic is discussed. Additionally, the work is focused on the description of the gait laboratory and the definition of the indexes in order to quantify patient´s overall gait in kinematic analysis. In the practical part, kinematic data analysis was implemented in the MATLAB environment and the results of healthy individuals and patients with cerebral palsy were compared. Kinematic analysis included peak detection in specific kinematic variables. In the last part a graphical user interface for visualization was implemented.