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Optimisation of regularisation methods for differentiation of measurement data in monitoring of human movements

机译:对人体运动监测测量数据分化的正则化方法的优化

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The research reported in this paper is related to the regularised differentiation of measurement data from impulse-radar sensors and infrared depth sensors applied in systems for unobtrusive monitoring of elderly persons. Four strategies for selection of regularisation parameters are compared in terms of their potential of decreasing the uncertainty of walking velocity estimation. The comparison is based on synthetic and real-world data. The best results are obtained by means of a strategy based on the so-called Stein's unbiased risk estimator.
机译:本文报道的研究与脉冲 - 雷达传感器的测量数据的正则化分化有关,该测量数据和用于在系统的系统中应用于不引人注目的老年人的监测。在减少步行速度估计的不确定性的可能性方面比较了四种正则化参数选择的四种策略。比较基于合成和现实世界数据。通过基于所谓的Stein的无偏见风险估算器的策略来获得最佳结果。

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