Personnel characteristics identification based on foot induced structural vibration

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Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (23) : 249-256.

HOU Xingmin, LI Ran, ZHANG Yujie

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Abstract

Identity recognition is an important work in the field of security. At present, the methods based on biometrics are mainly static physiological characteristics. However, there are relatively few researches on the use of foot vibration signal for identity recognition. In this paper, we use the difference of vibration signals caused by different people's foot induced structure to identify individuals. Firstly, footstep events and non-footstep events are detected based on energy threshold method, and then 16 footstep characteristic parameters of single footstep events of different testers are compared and analyzed in time domain and frequency domain. it is found that the parameter differences under different feature combinations can be used as the basis for identity identification. In order to verify the effectiveness of the method, support vector machine (SVM) is used as a classification tool. In a quiet test environment, without considering the influence of testers' shoes, the average recognition rates of the three experimental cases are 79.21%, 91% and 96%, respectively. The results show that the effective combination of footstep feature parameters is suitable for identity recognition under small samples.
Key words: Identification; Foot vibration signal; Event detection; Feature extraction; Support vector machines

Key words

Identification / Foot vibration signal / Event detection / Feature extraction / Support vector machines

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HOU Xingmin, LI Ran, ZHANG Yujie. Personnel characteristics identification based on foot induced structural vibration[J]. Journal of Vibration and Shock, 2022, 41(23): 249-256

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