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Vol: 59(73) No: 1 / June 2014 Personal Profile-Based Sport Activity Risk Assessment with Reduced Computational Needs Edit Tóth-Laufer Institute of Mechatronics and Vehicle Engineering, Óbuda University, Budapest, Népszínház u. 8, 1081 Budapest, Hungary, phone: (+36 1) 666-5377, e-mail: laufer.edit@bgk.uni-obuda.hu Keywords: fuzzy logic, Mamdani-type inference, complexity reduction, risk assessment, optimization Abstract In patient monitoring systems the patient specificity is essential to obtain realistic results, but its implementation is a major challenge in real systems. In this paper the author presents a fuzzy reasoning-based risk assessment framework, which evaluates the risk level of sport activity in real-time. The aim of the system is to achieve patient-specificity as much as it is possible using personal profile, which are stored in a database. Due to the real-time assessment the execution time is equally important, while the result should be accurate, within an allowed error limit. For this reason the inference structure modification is required, because the used conventional Mamdani-type inference, which can be used advantageously in these kinds of applications, is a computationally intensive task. In order to reduce the computational needs of the inference, the author proposes some modified versions of the conventional inference structure. In this way the obtained results are the same, while the advantages of the conventional system are retained and the computational complexity is reduced. References [1] M. Kozlovszky, J. Sicz-Mesziár, J. 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