OCCUPATIONAL APPLICATIONS
We investigated the association between shoe wear rate and several metrics describing an individual’s spatiotemporal gait characteristics (cadence, step length, and preferred walking speed). No associations were found, indicating that alternative metrics should be investigated to predict the individualized rate at which workers wear down shoe tread.
TECHNICAL ABSTRACT
Background
Shoe wear has been associated with increased slips and falls in the workplace. People wear down shoe tread at different rates; therefore, individualized shoe replacement timelines could improve resource targeting for organizations that use time as a basis for shoe replacement. Previous work has found that the shoe-floor kinetics, such as the friction requirements of walking, correlate with shoe wear rate. The use of easily measured metrics such as cadence, step length, or preferred walking speed to predict wear has not yet been investigated despite their relationship with friction requirements.
Purpose
This study seeks to determine the association between shoe wear rate and gait spatiotemporal characteristics.
Methods
Thirteen participants completed a longitudinal shoe wear study that consisted of a gait assessment followed by prolonged shoe wear in two pairs of slip-resistant shoes. The gait assessment was comprised of dry level-ground walking trials; kinematic and kinetic data were collected through optical motion capture and force plates. The participants’ mean cadence, step length, and preferred walking speed were calculated. The participants then wore their shoes at work; the shoe wear rate was determined by measuring the periodic volumetric tread loss during this wear-at-work portion of the study.
Results
Three linear regression models found no significant association between the chosen gait metrics and the shoe wear rate.
Conclusions
The lack of an association between the spatiotemporal gait characteristics and shoe wear rate indicates that these factors may not explain the differences in wear rate between participants. This negative finding suggests that other measures such as the required coefficient of friction are better for individualizing footwear replacement guidelines.
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Acknowledgments
The authors would like to acknowledge the lab manager of the Human Movement and Balance Laboratory, Jenna Trout, the consulting statistician, Dr. Natasa Vidic, and the students on the project who contributed to data collection through testing the shoes and coordinating with the participants: Ellen Martin, Bridget Moyer, Jessica Sider, Johanna Siegel, Vani Sundaram, Claire Tushak, & Paul Walter.