Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23814
Title: Low price foot pressure distribution screening technique: Optical podoscope with accurate foot print segmentation using hidden Markov random field model
Authors: Heravi, H
Ebrahimi, A
Nikzad, S
Olyaee, E
Salek Zamani, Y
Keywords: computer-assisted image processing;foot deformities;rehabilitation;hidden Markov random field
Issue Date: 1-Aug-2020
Publisher: Shiraz University of Medical Sciences
Citation: Heravi, H., Ebrahimi, A., Nikzad, S., Olyaee, E. and Salek Zamani, Y. (2020) 'Low Price Foot Pressure Distribution Screening Technique: Optical Podoscope with Accurate Foot Print Segmentation using Hidden Markov Random Field Model', Journal of Biomedical Physics and Engineering 10 (4), pp. 523 - 536. doi: 10.31661/jbpe.v0i0.618.
Abstract: Copyright © 2020 The Author(s). 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.
URI: https://bura.brunel.ac.uk/handle/2438/23814
DOI: https://doi.org/10.31661/jbpe.v0i0.618
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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