基于压力传感器矩阵足底分析的足部畸形诊断与健康风险预测

Jessie R. Balbin, J. D. De Guzman, Joaquin Gerard N. Trinidad, Francis Dominic S. Yaya
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引用次数: 1

摘要

脚是最容易被忽视的身体部位之一。如果治疗不当,足部健康通常会影响一个人的整体健康。本研究利用支持向量机和人工神经网络,通过使用名为Velostat的足底压力传感器矩阵来确定人的足部畸形。研究人员使用树莓派来运行使用Python编程的GUI。开发的设备将确定脚是正常的,高弓还是低弓。该测试在40名应答者中完成,在确定足部畸形方面准确率达到95%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Foot Deformity Determination and Health Risk Prediction Through Foot Plantar Analysis Using Pressure Sensor Matrix
One of the most overlooked parts of the body is the feet. Foot health can generally affect the overall health of a person if not treated well. This study utilized Support Vector Machines and an artificial neural network to determine the foot deformity of a person by using a foot plantar pressure sensor matrix called Velostat. The researchers used raspberry pi to run the GUI programmed using Python. The developed device will determine if the feet are normal, high arched, or low arched. The testing was done on 40 respondents and resulted in 95% accuracy in determining foot deformity.
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