Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA.
School of Information, University of Michigan, Ann Arbor, MI, USA.
Gait Posture. 2022 Oct;98:69-77. doi: 10.1016/j.gaitpost.2022.08.012. Epub 2022 Aug 19.
Walking speed strongly correlates with health outcomes, making accurate assessment essential for clinical evaluations. However, assessments tend to be conducted over short distances, often in a laboratory or clinical setting, and may not capture natural walking behavior. To address this gap, the following questions are investigated in this work: Is walking speed significantly influenced by the continuity and duration of a walking bout? Can preferred walking speed be inferred by grouping walking bouts using duration and continuity?
We collected two weeks of continuous data from fifteen healthy young adults using a thigh-worn accelerometer and a heart rate monitor. Walking strides were identified and grouped into walking periods. We quantified the duration and the continuity of each walking period. Continuity is used to parameterize changes in stepping rate related to pauses during a bout of walking. Finally, we analyzed the influence of duration and continuity on estimates of stride speed, and examined how the distribution of walking speed varies depending on different walking modes (defined by duration and continuity).
We found that continuity and duration can be used to explain some of the variability in real-world walking speed (p<0.001). Speeds estimated from long continuous walks with many strides (42% of all recorded strides) had the lowest standard deviation. Walking speed during these bouts was 1.41ms (SD = 0.26ms).
Walking behavior in the real world is largely variable. Features of real-world walks, like duration and continuity, can be used to explain some of the variability observed in walking speed. As such, we recommend using long continuous walks to confidently isolate the preferred walking behavior of an individual.
行走速度与健康结果密切相关,因此准确评估对于临床评估至关重要。然而,评估往往是在短距离内进行的,通常在实验室或临床环境中进行,并且可能无法捕捉到自然的行走行为。为了解决这一差距,本工作研究了以下问题:行走速度是否受到行走回合的连续性和持续时间的显著影响?是否可以通过使用持续时间和连续性对行走回合进行分组来推断出首选行走速度?
我们使用 thigh-worn 加速度计和心率监测器从十五名健康的年轻成年人那里收集了两周的连续数据。确定了行走步伐并将其分组为行走期。我们量化了每个行走期的持续时间和连续性。连续性用于参数化与行走回合中暂停相关的步频变化。最后,我们分析了持续时间和连续性对步速估计的影响,并研究了行走速度的分布如何取决于不同的行走模式(通过持续时间和连续性定义)。
我们发现连续性和持续时间可以解释一些真实世界行走速度的可变性(p<0.001)。从具有许多步伐(记录的所有步伐的 42%)的长连续行走中估计的速度具有最低的标准偏差。这些回合中的行走速度为 1.41ms(SD=0.26ms)。
现实世界中的行走行为在很大程度上是可变的。现实世界行走的特征,如持续时间和连续性,可以用来解释观察到的行走速度的一些可变性。因此,我们建议使用长的连续行走来自信地隔离个体的首选行走行为。