Mojmil Cecić

Quantitative human gait analysis

Abstract In this paper, the methodology for normal gait recognition and estimation is described. Normal gait recognition is derived on the basis of kinematics data of the human locomotion system. Measurements were carried out and the data were processed and statistically analyzed. The procedure was done on a group of 20 students. Kinematics data have been presented in phase plane. Sets of data in phase plane for the specific discrete moments in time were statistically processed using the Gaussian and Bootstrap methods. Discrete moments are chosen according to specific gait phases of a gait cycle. Finally, as a result of statistical analysis, the gait quality index (GQI) is obtained for each gait phase.

Motion analysis system for identification of 3D human locomotion kinematics data and accuracy testing

Abstract In this article, a procedure for acquisition and processing of the human locomotion system kinematics data is presented. Software for 3D motion analysis system is developed, discussed and described. Data acquisition was performed using two commercial camcorders, framegrabber and a personal computer. Data processing by direct linear transformation provided 3D coordinates of the measured movement. Inaccuracies due to the relatively low frame rate and non-synchronised cameras were improved using software. The results of laboratory testing are given, and confirm this improvement. The procedure for synchronisation error elimination is described in detail.

Comparison of Uncalibrated Model-Free Visual Servoing Methods for Small-Amplitude Movements: A Simulation Study

The paper compares the performance of several methods used for the estimation of an image Jacobian matrix in uncalibrated model-free visual servoing. This was achieved for an eye-in-hand configuration with small-amplitude movements with several sets of system parameters. The tested methods included the Broyden algorithm, Kalman and particle filters as well as the recently proposed population-based algorithm. The algorithms were tested in a simulation environment (Peter Corkes Robotic Toolbox for MATLAB) on a PUMA 560 robot. Several application scenarios were considered, including static point and dynamic trajectory tracking, with several characteristic shapes and three different speeds. Based on the obtained results, conclusions were drawn about the strengths and weaknesses of each method both for a particular setup and in general. Algorithm-switching was introduced and explored, since it might be expected to improve overall robot tracking performance with respect to the desired trajectory. Finally, possible future research directions are suggested.