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k24 630 Analysis of human body movement patterns and falls detection

28th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2024) Analysis of human body movement patterns and falls detection Abstract In the paper there are presented and discussed problems of applying the analytical techniques to extract required information from discrete biometric signal. In particular, there are presented results of research on a method to analyze the human body physical activity recording. The research is aimed to determine factors of body movement in three-dimensional space that can be used to detect selected situations, especially the dangerous ones, such as falls. In particular, there is analyzed whether the Poincaré plot- based statistical filtration can be effectively used as the analytical apparatus to detect potentially hazardous situations. Such research results are not publicly available and obtaining and publishing it will allow for designing and constructing the high-efficiency and low-cost microprocessor systems to detect and help to avoid the dangerous situations. Changes in age structure of contemporary societies are briefly discussed as the background and motivation for research. A review of human body activity monitoring techniques in terms of fall detection is presented, and analysis of such a signal is formalized. Auxiliary signal transform and data measures are proposed, analytic technique is presented and example of results are given. Research results overview is presented and conclusion is drawn, future work directions are proposed.