The Use of Arch Index to Characterize Arch Height: A Digital Image Processing Approach

Woei Chyn Chu, Shin Hwa Lee, William Chu, Tzyy Jiuan Wang, Maw Chang Lee

Research output: Contribution to journalArticlepeer-review

89 Scopus citations

Abstract

Attempts to evaluate foot arch types from footprint parameters have yielded conflicting results in the past This could be caused by the uncertainty inherent in the definition of some footprint parameters and the inaccuracy during the footprint acquisition and the parameter calculation phases of the traditional methods. In order to avoid these problems, digital image processing methods were used to acquire and to calculate the Arch Index (AI), a parameter which is robust in its definition. A significant correlation (r = −0.70, p < 0.0001) was found between AI and arch height Therefore this study confirms that foot arch type does correlate with the footprint parameter, AI. This was further revealed by a new parameter, the Modified Arch Index (MAI), which incorporates foot pressure information in the evaluation. MAI not only correlated well with arch height (r = −0.71, p < 0.0001) but appeared to characterize abnormal foot types better than AI.

Original languageEnglish
Pages (from-to)1088-1093
Number of pages6
JournalIEEE Transactions on Biomedical Engineering
Volume42
Issue number11
DOIs
StatePublished - Nov 1995

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