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基于角度、尺寸分析和图像处理技术的低计算成本足部畸形诊断传感器。

Low Computational-Cost Footprint Deformities Diagnosis Sensor through Angles, Dimensions Analysis and Image Processing Techniques.

机构信息

Unidad Académica de Ingeniería Biomédica, Universidad Politécnica de Sinaloa, Carretera Municipal Libre Mazatlán Higueras km 3, Col. Genaro Estrada, Mazatlán Sin. 82199, Mexico.

Center for Biomedical Technology, Polythecnic University of Madrid, Campus Montegancedo, Pozuelo de Alarcón, Madrid 28223, Spain.

出版信息

Sensors (Basel). 2017 Nov 22;17(11):2700. doi: 10.3390/s17112700.

DOI:10.3390/s17112700
PMID:29165397
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5713009/
Abstract

Manual measurements of foot anthropometry can lead to errors since this task involves the experience of the specialist who performs them, resulting in different subjective measures from the same footprint. Moreover, some of the diagnoses that are given to classify a footprint deformity are based on a qualitative interpretation by the physician; there is no quantitative interpretation of the footprint. The importance of providing a correct and accurate diagnosis lies in the need to ensure that an appropriate treatment is provided for the improvement of the patient without risking his or her health. Therefore, this article presents a smart sensor that integrates the capture of the footprint, a low computational-cost analysis of the image and the interpretation of the results through a quantitative evaluation. The smart sensor implemented required the use of a camera (Logitech C920) connected to a Raspberry Pi 3, where a graphical interface was made for the capture and processing of the image, and it was adapted to a podoscope conventionally used by specialists such as orthopedist, physiotherapists and podiatrists. The footprint diagnosis smart sensor (FPDSS) has proven to be robust to different types of deformity, precise, sensitive and correlated in 0.99 with the measurements from the digitalized image of the ink mat.

摘要

手动测量足部人体测量学可能会导致误差，因为这项任务涉及到执行测量的专家的经验，从而导致同一个足迹产生不同的主观测量结果。此外，一些用于分类足部畸形的诊断是基于医生的定性解释；足迹没有定量解释。提供正确和准确诊断的重要性在于需要确保为改善患者的状况提供适当的治疗，而不会危及他或她的健康。因此，本文提出了一种智能传感器，该传感器集成了足迹采集、图像的低计算成本分析以及通过定量评估对结果的解释。所实现的智能传感器需要使用连接到 Raspberry Pi 3 的摄像头（Logitech C920），其中为图像的捕获和处理制作了图形界面，并将其适应于传统上由矫形医生、物理治疗师和足病医生等专业人员使用的足印器。足部诊断智能传感器（FPDSS）已被证明对不同类型的畸形具有鲁棒性、精确性、敏感性，并与油墨垫数字化图像的测量值相关度为 0.99。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/b094c9c2ad65/sensors-17-02700-g013a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/01748266b043/sensors-17-02700-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/cb22700ba025/sensors-17-02700-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/10982762d34d/sensors-17-02700-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/c0b3f3c83aa4/sensors-17-02700-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/57a11a9c1b2e/sensors-17-02700-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/c7cff152ab08/sensors-17-02700-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/b094c9c2ad65/sensors-17-02700-g013a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/01748266b043/sensors-17-02700-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/9582ff87c7be/sensors-17-02700-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/29035b5f24e5/sensors-17-02700-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/0660dde74c6b/sensors-17-02700-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/fa52b88c22af/sensors-17-02700-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/cb22700ba025/sensors-17-02700-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/10982762d34d/sensors-17-02700-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/c0b3f3c83aa4/sensors-17-02700-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/57a11a9c1b2e/sensors-17-02700-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/c7cff152ab08/sensors-17-02700-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c44a/5713009/b094c9c2ad65/sensors-17-02700-g013a.jpg

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3
Comparison between Staheli index on Harris mat footprint and Talar-first metatarsal angle for the diagnosis of flatfeet.基于哈里斯足底印记的斯塔赫利指数与距骨-第一跖骨角在扁平足诊断中的比较。
J Med Assoc Thai. 2014 Feb;97 Suppl 2:S131-5.
4
Comparing 3D foot scanning with conventional measurement methods.比较 3D 足部扫描与传统测量方法。
J Foot Ankle Res. 2014 Oct 25;7(1):44. doi: 10.1186/s13047-014-0044-7. eCollection 2014.
5
Normality tests for statistical analysis: a guide for non-statisticians.用于统计分析的正态性检验：非统计学家指南。
Int J Endocrinol Metab. 2012 Spring;10(2):486-9. doi: 10.5812/ijem.3505. Epub 2012 Apr 20.
6
Does footprint depth correlate with foot motion and pressure?足印深度与足部运动和压力有关吗？
J R Soc Interface. 2013 Mar 20;10(83):20130009. doi: 10.1098/rsif.2013.0009. Print 2013 Jun 6.
7
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8
Opto-electronic system for detection of flat foot by using estimation techniques: study and approach of design.基于估计技术的扁平足检测光电系统：设计研究与方法
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:5768-71. doi: 10.1109/IEMBS.2010.5627842.
9
Visual assessment of foot type and relationship of foot type to lower extremity injury.足部类型的视觉评估及与下肢损伤的关系。
J Orthop Sports Phys Ther. 1991;14(2):70-4. doi: 10.2519/jospt.1991.14.2.70.
10
The effect of foot type on in-shoe plantar pressure during walking and running.足部类型对步行和跑步时鞋内足底压力的影响。
Gait Posture. 2008 Oct;28(3):405-11. doi: 10.1016/j.gaitpost.2008.01.012. Epub 2008 Mar 11.