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Effectiveness of Variable-Gain Kalman Filter Based on Angle Error Calculated from Acceleration Signals in Lower Limb Angle Measurement with Inertial Sensors

机译：基于惯性传感器的加速信号计算可变增益卡尔曼滤波器的有效性

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The wearable sensor system developed by our group, which measured lower limb angles using Kalman-filtering-based method, was suggested to be useful in evaluation of gait function for rehabilitation support. However, it was expected to reduce variations of measurement errors. In this paper, a variable-Kalman-gain method based on angle error that was calculated from acceleration signals was proposed to improve measurement accuracy. The proposed method was tested comparing to fixed-gain Kalman filter and a variable-Kalman-gain method that was based on acceleration magnitude used in previous studies. First, in angle measurement in treadmill walking, the proposed method measured lower limb angles with the highest measurement accuracy and improved significantly foot inclination angle measurement, while it improved slightly shank and thigh inclination angles. The variable-gain method based on acceleration magnitude was not effective for our Kalman filter system. Then, in angle measurement of a rigid body model, it was shown that the proposed method had measurement accuracy similar to or higher than results seen in other studies that used markers of camera-based motion measurement system fixing on a rigid plate together with a sensor or on the sensor directly. The proposed method was found to be effective in angle measurement with inertial sensors.
机译：我们基团开发的可穿戴传感器系统，使用基于卡尔曼滤波的方法测量了下肢角度的下肢角度，以在评估康复支持的步态函数方面是有用的。但是，预计会降低测量误差的变化。本文提出了一种基于加速度信号计算的角度误差的可变卡尔曼增益方法，以提高测量精度。测试了所提出的方法，比较与固定增益卡尔曼滤波器和基于先前研究中使用的加速度幅度的可变卡尔曼增益方法。首先，在跑步机行走中的角度测量，所提出的方法测量了具有最高测量精度的下肢角度，并改善了脚踏倾斜角度测量的显着倾斜角度测量，而其改进了略微柄和大腿倾角。基于加速度幅度的可变增益方法对我们的卡尔曼滤波器系统无效。然后，在刚体模型的角度测量中，示出了该方法的测量精度与在其他研究中看到的结果类似的测量精度，这些方法与传感器一起固定在刚性板上的基于相机的运动测量系统的标记或直接在传感器上。发现所提出的方法以与惯性传感器的角度测量有效。

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