University of Michigan, Mechanical Engineering, Ann Arbor, MI 48109, USA.
University of Michigan, Robotics, Ann Arbor, MI 48109, USA.
J Exp Biol. 2024 Jul 1;227(13). doi: 10.1242/jeb.246181.
Speeds that minimize energetic cost during steady-state walking have been observed during lab-based investigations of walking biomechanics and energetics. However, in real-world scenarios, humans walk in a variety of contexts that can elicit different walking strategies, and may not always prioritize minimizing energetic cost. To investigate whether individuals tend to select energetically optimal speeds in real-world situations and how contextual factors influence gait, we conducted a study combining data from lab and real-world experiments. Walking kinematics and context were measured during daily life over a week (N=17) using wearable sensors and a mobile phone. To determine context, we utilized self-reported activity logs, GPS data and follow-up exit interviews. Additionally, we estimated energetic cost using respirometry over a range of gait speeds in the lab. Gross and net cost of transport were calculated for each participant, and were used to identify energetically optimal walking speed ranges for each participant. The proportion of real-world steady-state stride speeds within these ranges (gross and net) were identified for all data and for each context. We found that energetically optimal speeds predicted by gross cost of transport were more predictive of walking speeds used during daily life than speeds that would minimize net cost of transport. On average, 82.2% of all steady-state stride speeds were energetically optimal for gross cost of transport for all contexts and participants, while only 45.6% were energetically optimal for net cost of transport. These results suggest that while energetic cost is a factor considered by humans when selecting gait speed in daily life, it is not the sole determining factor. Context contributes to the observed variability in movement parameters both within and between individuals.
在基于实验室的行走生物力学和能量学研究中，已经观察到在稳态行走过程中最小化能量消耗的速度。然而，在现实世界的场景中，人类在各种情况下行走，可能会采用不同的行走策略，并且不一定总是优先考虑最小化能量消耗。为了研究个体在现实情况下是否倾向于选择能量最优的速度，以及环境因素如何影响步态，我们进行了一项结合实验室和真实世界实验数据的研究。使用可穿戴传感器和手机，在一周的日常生活中（N=17）测量了行走运动学和环境。为了确定环境，我们利用了活动日志、GPS 数据和后续的退出访谈。此外，我们还在实验室中使用呼吸计在一系列步态速度下估计能量消耗。为每个参与者计算了总运输成本和净运输成本，并用于确定每个参与者的能量最优行走速度范围。确定了所有数据和每个环境中这些范围内（总运输成本和净运输成本）的真实世界稳态步速比例。我们发现，总运输成本预测的能量最优速度比最小化净运输成本的速度更能预测日常生活中的行走速度。平均而言，所有环境和参与者的总运输成本的所有稳态步速中，有 82.2%是能量最优的，而净运输成本的能量最优比例仅为 45.6%。这些结果表明，虽然能量消耗是人类在日常生活中选择步态速度时考虑的因素之一，但它不是唯一的决定因素。环境会导致个体内和个体间的运动参数存在可观察到的变异性。
