Low Price Foot Pressure Distribution Screening Technique: Optical Podoscope with Accurate Foot Print Segmentation using Hidden Markov Random Field Model

Abstract

Background: Foot pressure assessment systems are widely used to diagnose foot pathologies. The human foot plays an important role in maintaining the biomechanical function of the lower extremities which includes the provision of balance and stabilization of the body during gait. Objective: There are different types of assessment tools with different capabilities which are discussed in detail in this paper. In this project, we introduce a new camera-based pressure distribution estimation system which can give a numerical estimation in addition to giving a visual illustration of pressure distribution of the sole. Material and Methods: In this analytical study we proposed an accurate Foot Print segmentation using hidden Markov Random Field model. In the first step, an image is captured from the traditional Podoscope device. Then, the HMRF-EM image segmentation scheme applies to extract the contacting part of the sole to the ground. Finally, based on a simple calibration method, per mm2, pressure estimates to give an accurate pressure distribution measure. Results: A significant and usable estimation of foot pressure has been introduced in this article. The main drawback of introduced systems is the low resolution of sensors which is solved using a high resolution camera as a sensor. Another problem is the patchy edge extracted by the systems which is automatically solved in the proposed device using an accurate image segmentation algorithm.Conclusion: We introduced a camera-based plantar pressure assessment tool which uses HMRF-EM-based method has been explained in more detail which gives a brilliant sole segmentation from the captured images.

Keywords

• image processing, computer-assisted
• foot deformities
• rehabilitation
• hidden markov random field