Detecting pediatric foot deformities using plantar pressure measurements: A semi-supervised approach

K. Ramakrishna Kini; Muddu Madakyaru; Fouzi Harrou; Ying Sun

doi:10.1109/MDAT.2023.3234224

Detecting pediatric foot deformities using plantar pressure measurements: A semi-supervised approach

K. Ramakrishna Kini
, Muddu Madakyaru
, Fouzi Harrou
, Ying Sun

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

This article presents a semisupervised machine learning approach to identify pediatric foot deformities using foot plantar pressure measurements. It synergistically combines the benefits of PCA for feature extraction and the Kantorovich distance to handle deformities.

Original language	English
Pages (from-to)	61-68
Number of pages	8
Journal	IEEE Design and Test
Volume	40
Issue number	4
DOIs	https://doi.org/10.1109/MDAT.2023.3234224
Publication status	Published - 01-08-2023

All Science Journal Classification (ASJC) codes

Software
Hardware and Architecture
Electrical and Electronic Engineering

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10.1109/MDAT.2023.3234224

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title = "Detecting pediatric foot deformities using plantar pressure measurements: A semi-supervised approach",

abstract = "This article presents a semisupervised machine learning approach to identify pediatric foot deformities using foot plantar pressure measurements. It synergistically combines the benefits of PCA for feature extraction and the Kantorovich distance to handle deformities.",

author = "Kini, \{K. Ramakrishna\} and Muddu Madakyaru and Fouzi Harrou and Ying Sun",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",

year = "2023",

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doi = "10.1109/MDAT.2023.3234224",

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T1 - Detecting pediatric foot deformities using plantar pressure measurements

T2 - A semi-supervised approach

AU - Kini, K. Ramakrishna

AU - Madakyaru, Muddu

AU - Harrou, Fouzi

AU - Sun, Ying

PY - 2023/8/1

Y1 - 2023/8/1

N2 - This article presents a semisupervised machine learning approach to identify pediatric foot deformities using foot plantar pressure measurements. It synergistically combines the benefits of PCA for feature extraction and the Kantorovich distance to handle deformities.

AB - This article presents a semisupervised machine learning approach to identify pediatric foot deformities using foot plantar pressure measurements. It synergistically combines the benefits of PCA for feature extraction and the Kantorovich distance to handle deformities.

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UR - https://www.scopus.com/pages/publications/85147201067#tab=citedBy

U2 - 10.1109/MDAT.2023.3234224

DO - 10.1109/MDAT.2023.3234224

M3 - Article

AN - SCOPUS:85147201067

SN - 2168-2356

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EP - 68

JO - IEEE Design and Test

JF - IEEE Design and Test

IS - 4

ER -

Detecting pediatric foot deformities using plantar pressure measurements: A semi-supervised approach

Abstract

All Science Journal Classification (ASJC) codes

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