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.
展开▼
机译：手动测量脚部人体测量法可能会导致错误，因为此任务需要执行这些操作的专家的经验，从而导致同一足迹中的主观测量方法不同。此外，给出的一些对脚印变形进行分类的诊断是基于医师的定性解释。没有足迹的定量解释。提供正确和准确的诊断的重要性在于，需要确保提供适当的治疗方法来改善患者而不冒其健康风险。因此，本文提出了一种智能传感器，该传感器集成了足迹的捕获，图像的低计算成本分析以及通过定量评估对结果的解释。实施的智能传感器需要使用连接到Raspberry Pi 3的摄像头（Logitech C920），在该摄像头上制作了图形界面来捕获和处理图像，并使其适应了骨科专家等传统上使用的脚镜。 ，物理治疗师和足病医生。印记诊断智能传感器（FPDSS）已被证明对各种类型的变形，精确，灵敏并且与0.99倍的墨垫数字化图像测量结果相关性强。
展开▼
