University of Groningen, University Medical Center Groningen, Department of Human Movement Sciences, Groningen, the Netherlands; Université Grenoble-Alpes, AGEIS, Grenoble, France.
Université Grenoble-Alpes, AGEIS, Grenoble, France; Institut Universitaire de France, Paris, France; LabCom Telecom4Health, Orange Labs & Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP-UGA, Grenoble, France.
Hum Mov Sci. 2023 Jun;89:103075. doi: 10.1016/j.humov.2023.103075. Epub 2023 Mar 20.
Analysing gait in controlled conditions that resemble daily life walking could overcome the limitations associated with gait analysis in uncontrolled real-world conditions. Such analyses could potentially aid the identification of a walking condition that magnifies age-differences in gait. Therefore, the aim of the current study was to determine the effects of age and walking conditions on gait performance.
Trunk accelerations of young (n = 27, age: 21.6) and older adults (n = 26, age: 68.9) were recorded for 3 min in four conditions: walking up and down a university hallway on a track of 10 m; walking on a specified path, including turns, in a university hallway; walking outside on a specified path on a pavement including turns; and walking on a treadmill. Factor analysis was used to reduce 27 computed gait measures to five independent gait domains. A multivariate analysis of variance was used to examine the effects of age and walking condition on these gait domains.
Factor analysis yielded 5 gait domains: variability, pace, stability, time & frequency, complexity, explaining 64% of the variance in 27 gait outcomes. Walking conditions affected all gait domains (p < 0.01) but age only affected the time & frequency domain (p < 0.05). Age and walking conditions differently affected the domains variability, stability, time & frequency. The largest age-differences occurred mainly during straight walking in a hallway (variability: 31% higher in older adults), or during treadmill walking (stability: 224% higher, time&frequency: 120% lower in older adults).
Walking conditions affect all domains of gait independent of age. Treadmill walking and walking on a straight path in a hallway, were the most constrained walking conditions in terms of limited possibilities to adjust step characteristics. The age by condition interaction suggests that for the gait domains variability, stability, and time & frequency, the most constrained walking conditions seem to magnify the age-differences in gait.
在类似于日常生活行走的受控条件下分析步态可以克服在不受控制的真实世界条件下进行步态分析的局限性。这样的分析可能有助于确定一种放大步态随年龄变化的行走条件。因此，本研究的目的是确定年龄和行走条件对步态表现的影响。
记录 27 名年轻（年龄：21.6）和 26 名老年（年龄：68.9）成年人在 4 种条件下 3 分钟的躯干加速度：在 10m 的轨道上在大学走廊上上下行走；在大学走廊上按照特定路径行走，包括转弯；在包括转弯的大学走廊外的人行道上行走；以及在跑步机上行走。使用因子分析将 27 个计算出的步态测量值减少到 5 个独立的步态域。使用多元方差分析来检查年龄和行走条件对这些步态域的影响。
因子分析产生了 5 个步态域：变异性、步速、稳定性、时间和频率、复杂性，解释了 27 个步态结果中 64%的方差。行走条件影响所有步态域（p<0.01），但年龄仅影响时间和频率域（p<0.05）。年龄和行走条件对变异性、稳定性、时间和频率域有不同的影响。最大的年龄差异主要发生在走廊内的直走（变异性：老年人高出 31%），或在跑步机上行走（稳定性：老年人高出 224%，时间和频率：老年人低 120%）。
行走条件独立于年龄影响所有步态域。跑步机行走和在走廊内直行走是限制调整步幅特征可能性的最受限行走条件。年龄与条件的相互作用表明，对于变异性、稳定性和时间和频率这三个步态域，最受限的行走条件似乎会放大步态随年龄的差异。
