Biometrics Personal Identification by Wearable Pressure Sensor

• Published in: 2012 Fifth International Conference on Emerging Trends in Engineering and Technology pp. 120 - 123
• Main Authors: Takeda, Takahiro, Kuramoto, Kei, Kobashi, Syoji, Hata, Yutaka
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2012
• Subjects: Biometrics; Data mining; Euclidean distance; Feature extraction; Foot; Footwear; Legged locomotion; personal identification; pressure senor; Pressure sensors; Security; Sensors; walking; wearable sensor
• ISBN: 1479902764; 9781479902767
• ISSN: 2157-0477
• DOI: 10.1109/ICETET.2012.70

This article describes a personal identification method using dynamic foot pressure change while walking. This system acquires foot pressure change by wearable pressure sensor. The sensor has four sensing tips for the each foot, and these tips are fixed on shoes. In the experiment, we acquire eight steps pressure change data. The system extracts gait features from every step. The features are based on peak pressure value of each sensing tip. For all steps and all registered subjects, we calculate Euclidean distance between the feature and template of subject. The template is made from learning data of each registered person. For each step, the system chooses a registered person with the shortest Euclidean distance as a candidate of walking person. Then, the system counts selected number of the steps of a person. Finally, we identify the walking person by the larger number. The number less than threshold, identification of this walking person is failure. We employed 10 volunteers and identify them. In the experiment, we took pressure data 10 times for each volunteer. We used 3 data for learning and used the other 7 data for test data. The proposed method obtained 0.83% in FRR and 0.02% in FAR, when threshold parameter less than 3.