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首页> 外文期刊>Gait & posture >Inertial sensing algorithms for long-term foot angle monitoring for assessment of idiopathic toe-walking
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Inertial sensing algorithms for long-term foot angle monitoring for assessment of idiopathic toe-walking

机译：惯性感测算法，用于长期脚角监测，以评估特发性脚趾行走

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摘要

When children walk on their toes for no known reason, the condition is called Idiopathic Toe Walking (ITW). Assessing the true severity of ITW can be difficult because children can alter their gait while under observation in clinic. The ability to monitor the foot angle during daily life outside of clinic may improve the assessment of ITW. A foot-worn, battery-powered inertial sensing device has been designed to monitor patients' foot angle during daily activities. The monitor includes a 3-axis accelerometer, 2-axis gyroscope, and a low-power microcontroller. The device is necessarily small, with limited battery capacity and processing power. Therefore a high-accuracy but low-complexity inertial sensing algorithm is needed. This paper compares several low-complexity algorithms' aptitude for foot-angle measurement: accelerometer-only measurement, finite impulse response (FIR) and infinite impulse response (IIR) complementary filtering, and a new dynamic predict-correct style algorithm developed using fuzzy c-means clustering. A total of 11 subjects each walked 20. m with the inertial sensing device fixed to one foot; 10. m with normal gait and 10. m simulating toe walking. A cross-validation scheme was used to obtain a low-bias estimate of each algorithm's angle measurement accuracy. The new predict-correct algorithm achieved the lowest angle measurement error: <5° mean error during normal and toe walking. The IIR complementary filtering algorithm achieved almost-as good accuracy with less computational complexity. These two algorithms seem to have good aptitude for the foot-angle measurement problem, and would be good candidates for use in a long-term monitoring device for toe-walking assessment.
机译：当孩子不明原因走路时，这种情况称为特发性脚趾走路（ITW）。评估ITW的真实严重程度可能很困难，因为儿童在诊所观察时可以改变步态。在诊所以外的日常生活中监控脚角度的能力可能会改善对ITW的评估。设计了一种脚踏式电池供电的惯性传感设备，可在日常活动中监控患者的脚部角度。该监视器包括一个3轴加速度计，2轴陀螺仪和一个低功耗微控制器。该设备必须很小，电池容量和处理能力有限。因此，需要一种高精度，低复杂度的惯性传感算法。本文比较了几种低复杂度算法在脚角测量中的适用性：仅加速度计测量，有限冲激响应（FIR）和无限冲激响应（IIR）互补滤波，以及使用模糊C开发的新的动态预测正确样式算法-表示聚类。惯性传感装置固定在一只脚上，共有11名受试者各自走了20米。步态正常时为10. m，模拟脚趾行走时为10. m。使用交叉验证方案来获得每种算法的角度测量精度的低偏差估计。新的预测校正算法实现了最低的角度测量误差：正常和脚趾行走期间的平均误差<5°。 IIR互补滤波算法以几乎相同的精度实现了较低的计算复杂度。这两种算法似乎对脚角测量问题具有良好的适应性，并且将是用于脚趾行走评估的长期监测设备的良好候选者。

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