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Cross Pocket Gait Authentication Using Mobile Phone Based Accelerometer Sensor

  • Muhammad MuaazEmail author
  • René Mayrhofer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9520)

Abstract

Gait authentication using mobile phone based accelerometer sensors offers an implicit way of authenticating users to their mobile devices. This study explores gait authentication performance under a realistic scenario if gait template and gait test data belongs to left and right side front pocket of the trousers. To simulate this scenario, we used two identical (model, build, and vendor) Android mobile phones to record cross pocket biometric gait data from 35 participants (29 male and 6 female) in two different sessions. Both datasets (left and right pocket) are processed and segmented using the same approach. Our results show that biometric gait performance not only decreases over the time but it is also highly influenced by the placement of the mobile device or the sensor capturing gait data. High number of False Non Matches (FNMR) in cross pocket scenario indicate a significant asymmetry in leg muscle strength.

Keywords

Mobile Phone Gait Cycle Dynamic Time Warping Global Threshold Mobile Phone User 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We gratefully acknowledge funding and support by the Christian Doppler Gesellschaft, A1 Telekom Austria AG, Drei-Banken-EDV GmbH, LG Nexera Business Solutions AG, and NXP Semiconductors Austria GmbH.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.JRC u’smile and Institute of Networks and SecurityJohannes Kepler University LinzLinzAustria

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