一种基于足压数据主成分分析的足弓形态智能检测方法研究
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1.复旦大学工程与应用技术研究院;2.复旦大学附属华山医院

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An Intelligent Arch Diagnostic Method Based on PCA on Plantar Pressure Distribution
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    摘要:

    目的 根据临床中平足与高弓足量化评估的要求,本课题提出一种基于足压数据主成分分析的智能快速足弓形态检测方法,并验证其临床有效性。方法 本研究纳入诊断为足弓异常与足弓健康的志愿者,设计研发了一套便携式足弓智能检测系统。采用44×52阵列式薄膜压阻传感器,采集静态站立式足底压力分布数据,利用自行编写的主成分分析算法自动拟合足轴线,进行足弓诊断并生成诊断报告。将足压采集结果与现有设备进行比对,验证足压数据的准确性。对于平足、高弓足和正常三类足弓的判别算法,通过对比临床诊断验证评估准确性。结果 该系统与现有压力采集设备的测量结果具有较好的相关性,接触面积偏差低于3.2%,计算拟合的足轴线与临床定义角度偏差小于1°,且该系统能获得与临床中足弓形态诊断相符率92.6%的评估结果。结论 本文引入主成分分析对足轴线自动化拟合,实现了快速而准确提取足弓信息的目的。该方法可用于临床实践中平足与高弓足的辅助筛查,有助于开展足弓畸形程度的量化分析和病理机制的研究。

    Abstract:

    Objective According to clinical demand of quantification evaluation on flat-foot and high-arch, to develop an intelligent and rapid method that diagnoses the form of the foot arch based on PCA, and to verify the validity of the system. Methods Choose a group of volunteers with abnormal foot arch and another group with healthy foot arch, implement a system based on plantar pressure measurement to evaluate the foot arch, and verify whether the result is consistent with the clinical diagnose. The Plantar pressure measurement platform is based on a thin-firm piezoresistive sensor array with 44 rows, 52 columns of sensing units and a sampling frequency at 15 Hz. The data is transferred to PC host computer through USB, and the diagnosis and corresponding report are made on the host computer. The above system was compared with the existing plantar pressure acquisition device to verify the precision of collected data. PCA is performed on plantar pressure in order to automatically fit the foot axis, and the result is compared with clinical defined axis. Finally, the method was used for the diagnosis of volunteers with flat foot, high arch foot and normal foot arch to verify the accuracy, each of the 3 groups is consist of 3 volunteers. Results The deviation of the contact area acquired by the system compared to that of an existing plantar pressure acquisition device is less than 3.2%. The angle deviation of the fitted foot axis compared to the clinical defined axis is less than 1°. For 3 groups of volunteers, the system is capable of making a diagnosis that is 92.6% consistent with the clinical diagnosis. Conclusions By introducing the principal component analysis to automatically fit the foot axis, extracted the foot arch from the pressure footprint in a similar way to clinical manual way, developed a quantification evaluation method on form of foot arch and evaluated the validity of the result. The method can be used to assist the clinical diagnosis of flat foot and high arch foot, and help to understand the pathogenesis of foot arch deformity.

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  • 收稿日期:2021-03-17
  • 最后修改日期:2021-05-11
  • 录用日期:2021-05-14
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