Foot-type recognition algorithm based on plantar pressure images

doi:10.12307/2022.801

Abstract

Abstract: BACKGROUND: The arch of the foot plays a supporting and cushioning role in people’s daily physical activities. The abnormal arch of the foot can cause movement disorders and lower limb pain. It is the premise of making the corresponding prevention and nursing corrective measures to accurately identify the pathological foot type.
OBJECTIVE: The accuracy of foot recognition can be improved effectively by extracting common features of quadrupedal foot and designing foot interruption feature combined with gradient boosted decision tree classifier.
METHODS: Totally 1 710 plantar pressure images of 45 people were collected, including high-arch, flat and normal foot. Arch index, footprint index, arch width, and ratio index of plantar pressure images were extracted respectively. At the same time, the foot interruption feature was designed, and the gradient boosted decision tree algorithm was used to recognize different foot types of plantar pressure images.
RESULTS AND CONCLUSION: On the constructed data set of 1 710 plantar pressure images of 45 people, the average recognition accuracy of the proposed algorithm reached 96.43%, which was higher than the current commonly used methods based on arch index, footprint index, arch width, and ratio index.

Key words: foot-type recognition, foot-arch, high-arch, flat foot, foot type features, gradient boosted decision tree

CLC Number:

Bao Wenxia, Zhan Dongge, Wang Nian, Yang Xianjun, Ding Chengbiao. Foot-type recognition algorithm based on plantar pressure images[J]. Chinese Journal of Tissue Engineering Research, 2023, 27(4): 527-533.

Figures/Tables 4

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