A technique for the display of joint movement deviations.

Bulletin of prosthetics research Pub Date : 1980-01-01
R W Wirta, F L Golbranson
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Abstract

Detection of deviations in lower-limb joint movements derived during locomotion testing may be enhanced by displaying as a function of the gait cycle the algebraic difference between actual performance and a synthetic waveform. A synthetic waveform for a joint movement may be generated by applying Fourier series coefficients derived from a statistical treatment of test data characterizing the performance of normal healthy individuals walking at various velocities. Application of waveform specifics related to velocity yields a synthetic pattern serving as the criterion at the specific velocity demonstrated by a patient. The deviations, when plotted for the gait cycle, show the manner in which the actual waveform differs from the synthetic. At any increment of the gait cycle, the magnitude of the deviation and whether it is positive or negative can be determined. A positive deviation means that an expected angular position was exceeded, while a negative deviation means that an expected angular position was not reached. Individual signatures may be identified by the shape of the deviation pattern. Detection of the presence of oscillatory components in joint movements may be enhanced. Deviation patterns, developed from joint movements monitored bilaterally, often reveal compensatory activity with regard to the relative performances of the ipsilateral and contralateral limbs. Deviation amplitudes exceeding statistically determined boundaries for the synthetic waveform (e.g., two standard deviations) at specific zones of the support or wing phases facilitate identification of dysfunction. This paper describes the technique for deriving the deviation pattern, and touches upon its potential utility in evaluating locomotory performance of patients.

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一种显示关节运动偏差的技术。
通过显示实际表现与合成波形之间的代数差异作为步态周期的函数,可以增强在运动测试中得出的下肢关节运动偏差的检测。通过应用傅立叶级数系数,可以生成关节运动的合成波形,该系数来源于对表征正常健康个体以不同速度行走的性能的测试数据的统计处理。应用与速度相关的波形特性产生一个合成模式,作为患者所证明的特定速度的判据。当为步态周期绘制时,偏差显示了实际波形与合成波形不同的方式。在步态周期的任意增量处,可以确定偏差的大小以及是正的还是负的。正偏差意味着超出了预期的角度位置,而负偏差意味着没有达到预期的角度位置。单个特征可以通过偏离图案的形状来识别。可以加强对关节运动中振荡成分存在的检测。从双侧监测的关节运动发展而来的偏离模式,往往揭示了同侧和对侧肢体相对表现的代偿活动。在支撑或机翼阶段的特定区域,超过统计确定的合成波形边界的偏差幅度(例如,两个标准差)有助于识别功能障碍。本文描述了偏差模式的推导技术,并探讨了其在评估患者运动表现方面的潜在效用。
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