Details

Autor(en) / Beteiligte

• Baroudi, Loubna
• Yan, Xinghui
• Newman, Mark W.
• Barton, Kira
• Cain, Stephen M.
• Shorter, K. Alex

Titel

Investigating walking speed variability of young adults in the real world

Ist Teil von

• Gait & posture, 2022-10, Vol.98, p.69-77

Ort / Verlag

England: Elsevier B.V

Erscheinungsjahr

2022

Quelle

MEDLINE

Beschreibungen/Notizen

• 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−1 (SD = 0.26ms−1). 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. •Walking speed varied significantly with duration and continuity.•Long continuous walks may best capture preferred walking speed.•Real-world walking data can be parsed using the framework herein.•This framework can be extended for persistent monitoring of clinical populations.