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Articles

Women perception of shoe cushioning as a function of mechanical properties of footwear using a sensory trained panel method

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Pages 11-19 | Received 08 Sep 2017, Accepted 08 Nov 2017, Published online: 28 Nov 2017
 

Abstract

Most of the studies investigated footwear cushioning through the quantification of impact load or running-related injuries. Few studies focused on users’ perception of footwear cushioning. Users’ perception is usually investigated in other domains like food and consumer products using the ‘Sensory Trained Panel’ method. The purpose of this study was to assess the relationship between women's perception of shoe cushioning and mechanical properties of running shoes using a sensory trained panel approach. An initial mechanical characterization enabled to select 10 shoes having a wide range of mechanical properties. Ten recreational women runners were trained to become a ‘Sensory Trained Panel.’ First, simple vocabulary and gestures were highlighted to make shoe feature definition explicit and understood by all participants. Then, participants were trained to become discriminant, repeatable and in consensus for the rating of a given shoe feature. Finally, after running with a shoe model, participants rated the shoe feature intensity on a linear scale. The order of shoe models was balanced to avoid any effect of rank, sequence and fatigue. Each footwear model was available in four copies to limit alterations of shoe properties due to repetitive use. All the shoe models were blinded to avoid any effect of shoe design on the sensory evaluation. ‘Heel penetration’ was the explicit shoe feature understood by all participants to describe shoe cushioning. Panel performances were statistically verified. A significant correlation was highlighted and enabled to predict users’ perception of heel penetration based on shoe absolute maximal compression (r = 0.86, p = 6.9 × 10−4). The sensory trained panel method seemed powerful to quantify the perception of shoe features and could be used for other purposes than correlation between sensory and mechanical data.

Acknowledgements

Authors would like to thank Perrine Baudry for her support, and their colleagues Damien Fournet, Alexis Herbaut, Estelle Le Gendre and Cédric Morio for proof-reading the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

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