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基于惯性测量单元(IMU)的长达数小时的手臂运动跟踪的角度测量稳定性和周期计数准确性及其在正常肩部日常生活活动中的应用

Angle measurement stability and cycle counting accuracy of hours-long duration IMU based arm motion tracking with application to normal shoulder ADLs.

作者信息

Kirking Bryan

机构信息

Enovis, 9801 Metric Blvd, Austin, TX 78758, United States.

出版信息

Gait Posture. 2023 Feb;100:27-32. doi: 10.1016/j.gaitpost.2022.11.020. Epub 2022 Dec 1.

Abstract

BACKGROUND

Inertial measurement units are increasing used for monitoring joint motion, but there is a need to demonstrate their suitability during hours-long continuous use, as well as a need for validated methods to count arm cycles and provide descriptions of typical cycles.

RESEARCH QUESTION

Do IMU sensors and rainflow counting have sufficient accuracy for tracking and cycle counting of hours-long continuous arm motion? If so, what are the cycle rates of normal arm ADL and is there a representative cycle that can serve as a 'gait cycle' for the arm?

METHODS

IMU sensors continuously tracked a robot performing 8 h of simulated cyclic arm motion. Error in the angle measurements was regressed against time to determine the rate of error and the total accumulated error. Additionally, the cycle count accuracy of rainflow, peak/valley, and Fourier transform counting methods was evaluated.

RESULTS

Over 8 h the IMU measurements accumulated a maximum 0.473° of error and the rainflow method counted cycles with less than 1% error. Applying rainflow counting to normal shoulder ADL resulted in an average rate of 533 elevation cycles per day.Tabulating the ADL cycles by mean and range values into a matrix and calculating the centroid, the single best values representing arm elevation cycles were a mean of 22.4° and a range of 21.6°.

SIGNIFICANCE

IMU sensors can track arm motion for 8 h with little increase in error, though during longer durations error may reach unacceptable levels. For normal arm ADL, the rainflow determined count of arm elevation full-cycles differed from previous estimates based on peak/valley counting. From the rainflow counting, a single cycle representation of cycle mean and range was determined that can be used as a 'gait cycle' for the shoulder.

摘要

背景

惯性测量单元越来越多地用于监测关节运动,但需要证明其在长达数小时的连续使用期间的适用性,同时也需要经过验证的方法来计算手臂运动周期并描述典型周期。

研究问题

惯性测量单元(IMU)传感器和雨流计数法对于长达数小时的连续手臂运动跟踪和周期计数是否具有足够的准确性?如果是,正常手臂日常生活活动(ADL)的周期频率是多少,是否存在一个可作为手臂“步态周期”的代表性周期?

方法

IMU传感器连续跟踪一个执行8小时模拟循环手臂运动的机器人。将角度测量中的误差与时间进行回归分析,以确定误差率和总累积误差。此外,还评估了雨流计数法、峰谷计数法和傅里叶变换计数法的周期计数准确性。

结果

在8小时内,IMU测量的累积误差最大为0.473°,雨流计数法计数周期的误差小于1%。将雨流计数法应用于正常肩部ADL,结果显示平均每天有533次抬高周期。将ADL周期的均值和范围值制成矩阵并计算质心,代表手臂抬高周期的最佳单一值为均值22.4°和范围21.6°。

意义

IMU传感器可以跟踪手臂运动8小时,误差增加很少,不过在更长时间内误差可能达到不可接受的水平。对于正常手臂ADL,雨流计数法确定的手臂抬高全周期计数与先前基于峰谷计数的估计不同。通过雨流计数,确定了一个可以用作肩部“步态周期”的周期均值和范围的单一周期表示。

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