An Intelligent Arch Diagnostic Method Based on Principal Component Analysis of Plantar Pressure Distribution
10.16156/j.1004-7220.2022.03.21
- VernacularTitle:一种基于足压数据主成分分析的足弓形态智能检测方法
- Author:
Yanjie GU
1
;
Donggang JIANG
1
;
Siyuan LI
1
;
Xiang GENG
2
;
Wenming CHEN
1
;
Xin MA
2
Author Information
1. Academy for Engineering & Technology, Fudan University
2. Department of Orthopedics, Huashan Hospital, Fudan University
- Publication Type:Journal Article
- Keywords:
foot diagnosis;
plantar pressure;
principal component analysis (PCA);
flat foot;
high arch foot
- From:
Journal of Medical Biomechanics
2022;37(3):E518-E524
- CountryChina
- Language:Chinese
-
Abstract:
Objective According to clinical demand of quantification evaluation on flat foot and high arch, an intelligent and rapid method to diagnose arch shape based on principal component analysis (PCA) of plantar pressure is proposed, and its clinic validity is tested. Methods Volunteers diagnozed as abnormal arch and healthy arch were included in this study, and a portable intelligent arch test system was designed and developed. By adopting thin-firm piezoresistive sensor array with 44 rows, 52 columns of sensing units, the system could collect plantar pressure distribution data from the subjects under static standing. Foot axis could be fitted automatically by using the self-programmed PCA, so that foot diagnosis was completed with diagnostic report. The plantar pressure results from the system were compared with those from the existing plantar pressure acquisition device, so as to verify precision of collected data. The accuracy of the diagnosis algorithm for flat foot, high arch and healthy foot was verified through comparison with clinical diagnosis. Results The result of the system had a good correlation with that of the existing plantar pressure acquisition device, the deviation of contact area acquired by the system was smaller than 3.2%, and the angle deviation of the fitted foot axis with clinically defined angel was less than 1°. The system was capable of making diagnosis on arch shape that was 92.6% consistent with the clinical diagnosis. Conclusions PCA is introduced to automatically fit foot axis to achieve the purpose of fast and accurate extraction of foot arch information. The method can be used to assist clinical diagnosis of flat foot and high arch foot, and contribute to quantative analysis on foot arch deformity and its pathogenesis study.
