Literature DB >> 21660782

Towards an efficient and robust foot classification from pedobarographic images.

Francisco P M Oliveira1, Andreia Sousa, Rubim Santos, João Manuel R S Tavares.   

Abstract

This paper presents a new computational framework for automatic foot classification from digital plantar pressure images. It classifies the foot as left or right and simultaneously calculates two well-known footprint indices: the Cavanagh's arch index (AI) and the modified AI. The accuracy of the framework was evaluated using a set of plantar pressure images from two common pedobarographic devices. The results were outstanding, as all feet under analysis were correctly classified as left or right and no significant differences were observed between the footprint indices calculated using the computational solution and the traditional manual method. The robustness of the proposed framework to arbitrary foot orientations and to the acquisition device was also tested and confirmed.

Mesh:

Year:  2011        PMID: 21660782     DOI: 10.1080/10255842.2011.581239

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  2 in total

1.  Enhanced spatio-temporal alignment of plantar pressure image sequences using B-splines.

Authors:  Francisco P M Oliveira; João Manuel R S Tavares
Journal:  Med Biol Eng Comput       Date:  2012-11-08       Impact factor: 2.602

2.  A Deep-Learning Approach for Foot-Type Classification Using Heterogeneous Pressure Data.

Authors:  Jonghyeok Chae; Young-Jin Kang; Yoojeong Noh
Journal:  Sensors (Basel)       Date:  2020-08-11       Impact factor: 3.576

  2 in total

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