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Estimation of Uncertainties in 3D Motion Analysis Data

机译:3D运动分析数据的不确定性估算

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A complete understanding of motion is important for assisting clinicians and engineers in the prevention, diagnosis, and treatment of people with physical disorders. According to an ISO standard, three dimension (3D) motion measurements are always related to some errors and therefore always only obtained values. For 3D motion measurement systems, when applied to measuring human motion, motion data is sometimes reported with a standard error of measurement reflecting the uncertainty of the measurement caused by this skin movement artifact during motion as well as system error and marker noise. This lack of information seriously limits the ability to investigate motion analysis for the researchers. The purpose of this paper is to quantify the uncertainty caused by skin movement artifact as well as sensor noise and measurement error of the motion analysis system. We present a method for incorporating the uncertainty of the matching between a model of the calibration device (3D robot) and measurements, obtained with a motion analysis system (Optotrak Certus), in a Kalman filter.
机译:完全了解动议对于协助临床医生和工程师在预防,诊断和治疗有身体疾病的情况下是重要的。根据ISO标准,三维(3D)运动测量始终与某些错误相关,因此始终只获得值。对于3D运动测量系统,当应用于测量人类运动时,有时报告运动数据,其中测量标准误差反映了运动过程中这种皮肤运动伪像引起的测量的不确定性以及系统误差和标记噪声。这种缺乏信息严重限制了研究研究人员的运动分析的能力。本文的目的是量化皮肤运动伪影以及运动分析系统的传感器噪声和测量误差引起的不确定性。我们介绍了一种在卡尔曼滤波器中使用运动分析系统(OptoTrak Certus)获得的校准装置(3D机器人)和测量模型之间的匹配的不确定性的方法。

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