A New Biometric Identification System Based on Plantar Pressure

Biometric recognition based on physiological characteristics has been widely used for security reasons. In these systems, unique features, such as fingerprints, iris patterns, face structure, and voice, are used to recognize a person instead of codes that can be easily transferred. The biometric identification system based on plantar pressure proposed in this work applies a support vector machine (SVM) procedure to classify footprint patterns detected by a platform instrumented with fiber Bragg gratings (FBGs). Two sets of seven in- series gratings, with Bragg wavelengths within the 1526.96- and 1553.86-nm range, delimit two sensing regions corresponding to the left and right footprints. The coupled and nonlinear responses provided by the sensors are preprocessed and organized in a matrix. An algorithm based on SVM was used to extract and recognize foot features. The pattern recognition system constructed in this way returned hit rates greater than 86% for 12 classes, corresponding to different stepping patterns, with data not belonging to the training set.