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Concurrent Validity of an Automated Footprint Detection Algorithm to Measure Plantar Contact Area During Walking

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  • 1 Department of Kinesiology and Nutrition Sciences, University of Nevada Las Vegas, Las Vegas, NV.
  • | 2 École Supérieure d'Electronique de l'Ouest, Angers, France.
  • | 3 Department of Mechanical Engineering, University of Nevada Las Vegas, Las Vegas, NV.
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Background:

Monitoring footprints during walking can lead to better identification of foot structure and abnormalities. Current techniques for footprint measurements are either static or dynamic, with low resolution. This work presents an approach to monitor the plantar contact area when walking using high-speed videography.

Methods:

Footprint images were collected by asking the participants to walk across a custom-built acrylic walkway with a high-resolution digital camera placed directly underneath the walkway. This study proposes an automated footprint identification algorithm (Automatic Identification Algorithm) to measure the footprint throughout the stance phase of walking. This algorithm used coloration of the plantar tissue that was in contact with the acrylic walkway to distinguish the plantar contact area from other regions of the foot that were not in contact.

Results:

The intraclass correlation coefficient (ICC) demonstrated strong agreement between the proposed automated approach and the gold standard manual method (ICC = 0.939). Strong agreement between the two methods also was found for each phase of stance (ICC > 0.78).

Conclusions:

The proposed automated footprint detection technique identified the plantar contact area during walking with strong agreement with a manual gold standard method. This is the first study to demonstrate the concurrent validity of an automated identification algorithm to measure the plantar contact area during walking.

Corresponding author: Daniel E. Lidstone, MS, Department of Kinesiology and Nutrition Sciences, University of Nevada Las Vegas, 4505 S Maryland Pkwy, Las Vegas, NV 89154. (E-mail: lidstone@unlv.nevada.edu)