364 / 2021-07-14 21:00:00

Person identification utilizing vibration response of human fingers

Frequency Response Function,Human Body Vibration,Biometric Authentication,Biodynamics,Feature Extraction,Support Vector Machine,Machine Learning

Special Sessions > Human Vibration and Health Sensor Applications

This research suggests a new biometric identification approach in future personal devices that uses the frequency response of human body, especially fingers for personal identification. A series of experimental vibration modal analysis were conducted to measure frequency response functions (FRFs) of fingers of actual individuals. In addition, the major components of a finger such as phalanges, joints and skin were modeled in a biodynamic lumped system, and corresponding analytical FRFs were calculated for analytical modal analysis of finger for the comparison with the measured FRFs. In the identification process, an effective feature extraction method based on the correlation coefficient between frequency bins of measured FRFs was applied to extract the most effective set of frequency bins among all FRF spectrum. Extracted features were utilized to train support vector machine in the classification of the individuals. The classification results showed 99% accuracy at maximum in a controlled experimental setup, which verifies the feasibility of vibrational response as a new biometric identification of individuals.