Plantar pressure cartography reconstruction from 3 sensors

Abstract

Foot problem diagnosis is often made by using pressure mapping systems, unfortunately located and used in the laboratories. In the context of e-health and telemedicine for home monitoring of patients having foot problems, our focus is to present an acceptable system for daily use. We developed an ambulatory instrumented insole using 3 pressures sensors to visualize plantar pressure cartographies. We show that a standard insole with fixed sensor position could be used for different foot sizes. The results show an average error measured at each pixel of 0.01 daN, with a standard deviation of 0.005 daN.

Plantar Pressure‐Based Insole Gait Monitoring Techniques for Diseases Monitoring and Analysis: A Review

“…[ 15 ] Therefore, machine learning allows a sensing system with low sensing density to reconstruct the high‐resolution plantar pressure pattern map. [ 145,146 ]…”

“…Machine learning methods are utilized to determine the structure of the foot skeleton and elastic medium. [ 145 ] The information about the deviation of the plantar plate and the foot skeleton of the plantar pressure is obtained with the collected data from the three FSR sensors (arranged at the positions of the heel, first metatarsal, and fourth metatarsal), [ 146 ] and the pressure distribution is determined. [ 145 ] In this study, the average error is 2% of full scale with 0.1 N average error of each sensor, and the SD is 0.05 N (as shown in Figure 20b).…”