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The precise measurement and analysis of human movements is an essential step in biomechanical research used in sports or medicine. Measurement systems used for motion tracking should be non-invasive, safe to use, widely customisable and cost-efficient. In this study, complete design, development and evaluation of a high-speed optical motion tracking and analysis system is described. The system aims to analyse movements for sports and medical applications. The novelty of the proposed system is its design, which is based on visible light light-emitting diode (LED) markers, rather than infrared markers that are commonly used, and a pair of high-speed digital cameras. Calibration procedures and a super-resolution marker model are introduced, ensuring sub-pixel marker centre detection which results in higher three-dimensional reconstruction accuracy. Evaluation of the system included an accuracy test of the proposed system on static and moving objects with known dimensions, followed by analysis of kinematic data obtained in dynamic conditions while measuring human gait. The evaluation results are presented, and conclusions about system performance with possible improvements are discussed.

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Gait patterns of humans and humanoid robots are often described by analysing changes in angular rotation of hip, knee and ankle joints during one gait cycle. Each joint displays specific behaviour and irregularities of the gait pattern could be detected by measuring displacements from the normal rotation curve, while small deviations of individual gait characteristics are usually not easily detected. In this paper, an advanced gait analysis method is proposed, which incorporates analysis of angular data and its derivations of hip, knee, and ankle joints, presented in the phase plane. The gait kinematics was measured using a system based on active markers and fast digital cameras. The experiment included measurements on thirty healthy, barefoot humans while walking on a treadmill. We also simulated types of irregular gait, by measurements on subjects wearing knee constraints. The new kinematic parameters which are introduced clearly indicated the discrepancy between normal, healthy gait trials and irregular gait trials. The proposed gait factor parameter is a valuable measure for the detection of irregularities in gait patterns of humans and humanoid robots

Mobile phones have become ubiquitous in today's world. Their ever increasing computational power and sensing capabilities have made them well suited for number of tasks well beyond their original purpose of communication. But mobile phone usage while walking or driving can potentially be dangerous leading to serious injury or even death. In the paper we answer the question is it possible using only mobile phone's embedded accelerometer to detect changes in gait pattern caused by changed attention level due to interaction with mobile device like reading on-screen text. Experimental measurements were conducted on 8 test subjects in indoor environment with each test subject performing 6 trials. Two different approaches based on gait phase and gait velocity were tested on recorded data in batch mode with more promising one implemented in real-time manner. Obtained results are presented and discussed and possible future research directions outlined.