Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
Department of Physiotherapy, Tan Tock Seng Hospital, Singapore, Singapore.
PLoS One. 2018 Jun 18;13(6):e0199215. doi: 10.1371/journal.pone.0199215. eCollection 2018.
Deviation in gait performance from normative data of healthy cohorts is used to quantify gait ability. However, normative data is influenced by anthropometry and such differences among subjects impede accurate assessment. De-correlation of anthropometry from gait parameters and mobility measures is therefore desirable.
87 (42 male) healthy subjects varying form 21 to 84 years of age were assessed on gait parameters (cadence, ankle velocity, stride time, stride length) and mobility measures (the 3-meter/7-meter Timed Up-and-Go, 10-meter Walk Test). Multiple linear regression models were derived for each gait parameter and mobility measure, with anthropometric measurements (age, height, body mass, gender) and self-selected walking speed as independent variables. The resulting models were used to normalize the gait parameters and mobility measures. The normalization's capability in de-correlating data and reducing data dispersion were evaluated.
Gait parameters were predominantly influenced by height and walking speed, while mobility measures were affected by age and walking speed. Normalization de-correlated data from anthropometric measurements from |rs| < 0.74 to |rs| < 0.23, and reduced data dispersion by up to 69%.
Normalization of gait parameters and mobility measures through linear regression models augment the capability to compare subjects with varying anthropometric measurements.
与健康队列的标准数据相比，步态表现的偏差可用于量化步态能力。然而，标准数据受到人体测量学的影响，受试者之间的这种差异会阻碍准确的评估。因此，从步态参数和移动性测量中去相关人体测量学是可取的。
87 名（42 名男性）年龄在 21 至 84 岁之间的健康受试者接受了步态参数（步频、踝关节速度、步幅时间、步幅长度）和移动性测量（3 米/7 米计时起立行走、10 米步行测试）的评估。对于每个步态参数和移动性测量，使用多元线性回归模型，将人体测量学测量值（年龄、身高、体重、性别）和自我选择的步行速度作为自变量。使用这些模型对步态参数和移动性测量进行归一化。评估了归一化在去相关数据和减少数据分散方面的能力。
步态参数主要受身高和步行速度的影响，而移动性测量则受年龄和步行速度的影响。归一化通过线性回归模型将数据与人体测量学测量值去相关，相关系数从 |rs| < 0.74 降低到 |rs| < 0.23，并且数据分散度降低了高达 69%。
通过线性回归模型对步态参数和移动性测量进行归一化，可以增强对具有不同人体测量学测量值的受试者进行比较的能力。
