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

doi:10.1109/10.469375

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

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89 引文斯高帕斯（Scopus）

摘要

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.

原文	English
頁（從 - 到）	1088-1093
頁數	6
期刊	IEEE Transactions on Biomedical Engineering
卷	42
發行號	11
DOIs	https://doi.org/10.1109/10.469375
出版狀態	Published - 11月 1995

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title = "The Use of Arch Index to Characterize Arch Height: A Digital Image Processing Approach",

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.",

author = "Chu, {Woei Chyn} and Lee, {Shin Hwa} and William Chu and Wang, {Tzyy Jiuan} and Lee, {Maw Chang}",

note = "Funding Information: Manuscript received December 14. 1994, revised June 29, 1995. This work was supported by the Depamnent of Health, Taiwan. R.O.C. (Grant DOH& HR-409) and the National Science Council, Taiwan, R.O.C. (Grant NSC 83-0420-E-010-009). W. C. Chu, S. H. Lee, and M.C.Le e are with the Institute of Biomedical Engineering, National Yang-Ming University, Shih-Pai, Taipei, Taiwan 11221, R.O.C. W. Chu is with the Depamnent of olthoped~cs, Tri-Service General Hospital, Taipei, Taiwan, R.O.C. T.J. Wang is with the Department of Physical Therapy, National Yang-Ming University, Shih-Pai, Taipei, Taiwan 11221, R.O.C. IEEE Log Number 9414807.",

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

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