Biometric System by Foot Pressure Change Based on Neural Network

In this paper, we propose an approach to extract features of center of foot pressure (COP) obtained by a load distribution sensor and apply this method to develop a biometrics personal identification system. Biometrics technology, as a method of personal identification, plays an important role in ou...

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Bibliographic Details
Main Authors: Hong Ye, Kobashi, S., Hata, Y., Taniguchi, K., Asari, K.
Format: Conference Proceeding
Language:English
Subjects:
Biometrics
Biosensors
center of pressure
Data mining
Feature extraction
Foot
foot pressure
k-out-of-n system
load distribution sensor
neural network biometrics
Neural networks
Sensor phenomena and characterization
Sensor systems
System testing
Tactile sensors
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Description
Summary:In this paper, we propose an approach to extract features of center of foot pressure (COP) obtained by a load distribution sensor and apply this method to develop a biometrics personal identification system. Biometrics technology, as a method of personal identification, plays an important role in our daily lives. In our experiment, we have a user stand on load distribution sensor with slipper, and acquire pressure data during a simple motion, as touching a bell nearby by one hand but without movements of feet. We propose a biometrics personal identification system with less information, time and low space. First, we calculate the site of COP from the obtained pressure data. Features for identification are extracted from the position and the movement of COP. Second, we built a k-out-of-n system and a neural network (NN) model with the feature parameter. Third, we input test data to the two systems. Finally, we give a comparison of these two methods. We employ 11 volunteers. The experimental result reveals that the proposed identification method can achieve an accuracy of 12.0% in FRR (False Rejection Rate) and 1.0% in FAR (False Acceptance Rate).
ISSN:0195-623X
2378-2226
DOI:10.1109/ISMVL.2009.16