Kowalski Erik, Catelli Danilo S, Lamontagne Mario
Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.
Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada; Department of Orthopedic Surgery, The Ottawa Hospital, Ottawa, ON, Canada.
Gait Posture. 2022 Jun;95:176-182. doi: 10.1016/j.gaitpost.2022.04.022. Epub 2022 Apr 27.
To estimate gait variability, several methods have been routinely used which provide a measure of global variability. A recent study introduced a group waveform variability method which provides a point-by-point measurement of data variance equality. This can identify where in the gait cycle the significant differences in variability exist.
Do waveform differences exist in equality of variance and group means in lower limb biomechanical variables between healthy younger and older adults during a gait task?
Twenty healthy younger (19-44 years old, age=29.9(7.0) years, body mass index= 24.6(3.2)kg/m, females= 10) and 20 healthy older (55-79 years old, age=63.6(5.5) years, body mass index= 25.9(2.7)kg/m, females= 10) adults who were free from lower limb injuries and had no musculoskeletal or neurological disorders. Temporospatial outcomes, sagittal and frontal lower limb joint angles and moments, along with joint powers were examined as participants walked at a self-selected pace. Waveform patterns were normalized to the gait cycle and compared using equality of variance and statistical parametric mapping techniques.
No difference in walking speed existed between the younger or older groups (P > .05). The older group had greater variability (P < .05) in sagittal hip angles, as well as greater frontal ankle angle and moment variability. The younger group had significantly greater mean (P < .05) ankle power generation prior to toe-off.
This study provided a baseline of temporal differences in variance between healthy younger and older individuals. Its findings warrant the use of the equality of variance test to compare temporal differences for a variety of populations and tasks. Older adults generally had more variability than the younger adults, with many differences occurring near the transition from double- to single-limb support. The statistical parametric mapping analysis showed that the older adults could not generate as much ankle power as the younger adults prior to toe-off.
为了评估步态变异性，人们通常使用几种方法来提供整体变异性的度量。最近的一项研究引入了一种组波形变异性方法，该方法可对数据方差相等性进行逐点测量。这可以确定在步态周期的哪个位置存在变异性的显著差异。
在步态任务中，健康的年轻人和老年人在下肢生物力学变量的方差相等性和组均值方面是否存在波形差异？
选取20名健康的年轻人（年龄在19 - 44岁之间，平均年龄29.9(7.0)岁，体重指数24.6(3.2)kg/m²，女性10名）和20名健康的老年人（年龄在55 - 79岁之间，平均年龄63.6(5.5)岁，体重指数25.9(2.7)kg/m²，女性10名），他们下肢无损伤，无肌肉骨骼或神经系统疾病。当参与者以自选速度行走时，检查时空参数、矢状面和额状面下肢关节角度和力矩以及关节功率。将波形模式归一化到步态周期，并使用方差相等性和统计参数映射技术进行比较。
年轻组和老年组之间的步行速度没有差异（P > 0.05）。老年组在矢状面髋关节角度上具有更大的变异性（P < 0.05），以及更大的额状面踝关节角度和力矩变异性。年轻组在离地前踝关节产生的平均功率显著更大（P < 0.05）。
本研究提供了健康年轻人和老年人之间方差时间差异的基线。其研究结果表明，使用方差相等性检验来比较不同人群和任务的时间差异是合理的。老年人通常比年轻人具有更多的变异性，许多差异发生在从双下肢支撑到单下肢支撑的过渡阶段附近。统计参数映射分析表明，老年人在离地前不能像年轻人那样产生那么多的踝关节功率。
