Peak pressure analysis of foot plantar distribution based on image processing algorithm

Plantar pressure measurement is used to access the external loads, which interpreted in order to distinguish between normal and abnormal. Plantar pressure also provides valuable insight in gait analysis and pasture research. Several factors have been associated with the distribution of plantar foot pressure, including the body weight, age, foot structure, and standing/walking strategy.Foot ulceration due to diseasesis the main consideration because of the excessive foot plantar pressures in a particular area over time can give rise to such ulcers, but a lack in formulating accurately the distribution of pressure over the foot plantar and describing the relationship of the most parameters that effect on.The study objective is to examine the Body Mass Index through analyzing the relationships of seven levels of plantar pressure that distribute over the touch insole area with the four effective continuous predictor parameters (body mass, foot size, age,and gender), that have a direct effect on dynamic plantar pressure. The other main goal of this work is to create an algorithm which has the ability to formulate accurately and reliably the distribution of pressure over the foot plantar. Plantar pressure was profiled as an image at four measurement categories during standing and walking within two conditions of loading perspective; free, and loaded by carrying a simple weight during the subject inspect. Repeatability test together with the image processing tool is considered to classify seven levels of the plantar pressure and select the suitable category of measurements according to the relationships of each level with the studied parameters. The outcome of the repeatability test indicates that the dynamic with load (DL) is the best measurement category to consider in the plantar pressure data analysis. Seven levels of pressure have been successfully classified via image processing capabilities to simplify the creation of three modeling equations; polynomial, 3rd order, 5th, and 1st order equations to model each of the human body weight, foot size, and the age respectively. The present meta-analysis of the 79 subjects showed significant outcomes through the model equations that evaluated by R² values, where 0.866 for human body weight equation, 0.602 for the age equation, and 0.308 for the foot size equation, all of them are formulated as a function of plantar pressure values. The proposed image processing that based on the related parameters. Thus, the image information of the pressure sensor can solve the balancing problem for those who have a problem during standing and walking.

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