Improved Hip-Based Individual Recognition Using Wearable Motion Recording Sensor

In todays society the demand for reliable verification of a user identity is increasing. Although biometric technologies based on fingerprint or iris can provide accurate and reliable recognition performance, they are inconvenient for periodic or frequent re-verification. In this paper we propose a hip-based user recognition method which can be suitable for implicit and periodic re-verification of the identity. In our approach we use a wearable accelerometer sensor attached to the hip of the person, and then the measured hip motion signal is analysed for identity verification purposes. The main analyses steps consists of detecting gait cycles in the signal and matching two sets of detected gait cycles. Evaluating the approach on a hip data set consisting of 400 gait sequences (samples) from 100 subjects, we obtained equal error rate (EER) of 7.5% and identification rate at rank 1 was 81.4%. These numbers are improvements by 37.5% and 11.2% respectively of the previous study using the same data set.

[1]  Yangsheng Xu,et al.  Gait Modeling for Human Identification , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[2]  Heikki Ailisto,et al.  Identifying users of portable devices from gait pattern with accelerometers , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[3]  Einar Snekkenes,et al.  Arm Swing as a Weak Biometric for Unobtrusive User Authentication , 2008, 2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[4]  Mikko Lindholm,et al.  Identifying people from gait pattern with accelerometers , 2005, SPIE Defense + Commercial Sensing.

[5]  Patrick Bours,et al.  Eigensteps: A giant leap for gait recognition , 2010, 2010 2nd International Workshop on Security and Communication Networks (IWSCN).

[6]  Einar Snekkenes,et al.  Gait Recognition Using Wearable Motion Recording Sensors , 2009, EURASIP J. Adv. Signal Process..

[7]  Liu Ming,et al.  A Wearable Acceleration Sensor System for Gait Recognition , 2007, 2007 2nd IEEE Conference on Industrial Electronics and Applications.

[8]  Damjan Zazula,et al.  Gait identification using cumulants of accelerometer data , 2009 .

[9]  Uwe Hansmann,et al.  Pervasive Computing , 2003 .

[10]  Einar Snekkenes,et al.  Towards understanding the uniqueness of gait biometric , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[11]  Einar Snekkenes,et al.  Gait Authentication and Identification Using Wearable Accelerometer Sensor , 2007, 2007 IEEE Workshop on Automatic Identification Advanced Technologies.

[12]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Liu Ming,et al.  Identification of Individual Walking Patterns Using Gait Acceleration , 2007, 2007 1st International Conference on Bioinformatics and Biomedical Engineering.

[14]  Heikki Ailisto,et al.  Unobtrusive Multimodal Biometrics for Ensuring Privacy and Information Security with Personal Devices , 2006, Pervasive.

[15]  Mark S. Nixon,et al.  A floor sensor system for gait recognition , 2005, Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID'05).

[16]  Einar Snekkenes,et al.  Spoof Attacks on Gait Authentication System , 2007, IEEE Transactions on Information Forensics and Security.

[17]  Tom E. Bishop,et al.  Blind Image Restoration Using a Block-Stationary Signal Model , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[18]  Tieniu Tan,et al.  Human identification based on gait , 2005, The Kluwer international series on biometrics.

[19]  K. Taniguchi,et al.  Biometric personal identification based on gait pattern using both feet pressure change , 2008, 2008 World Automation Congress.

[20]  Yuting Zhang,et al.  Accelerometer-based gait recognition via voting by signature points , 2009 .

[21]  Carla Schlatter Ellis,et al.  Using Ground Reaction Forces from Gait Analysis: Body Mass as a Weak Biometric , 2007, Pervasive.

[22]  D. Alvarez,et al.  Comparison of Step Length Estimators from Weareable Accelerometer Devices , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  Stacy J. Morris,et al.  A shoe-integrated sensor system for wireless gait analysis and real-time therapeutic feedback , 2004 .