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Identifying Users of Portable Devices from Gait Pattern with Accelerometers
Abstract
Identifying users of portable devices from gait signals acquired with three-dimensional accelerometers was studied. Three approaches, correlation, frequency domain and data distribution statistics, were used. Test subjects (N=36) walked with fast, normal and slow walking speeds in enrolment and test sessions on separate days wearing the accelerometer device on their belt, at back. It was shown to be possible to identify users with this novel gait recognition method. Best equal error rate (EER=7%) was achieved with the signal correlation method, while the frequency domain method and two variations of the data distribution statistics method produced EER of 10%, 18% and 19%, respectively.
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Cited by
Zero Trust Architecture (ZTA): A Comprehensive Survey
Syed, N. F., Shah, S. W., Shaghaghi, A., Anwar, A., Baig, Z., & Doss, R. (2022) · IEEE Access · doi:10.1109/access.2022.3174679 · Cited by 406
“…use the raw data corresponding to a gait pattern (and then use correlation or machine learning for performing continuous authentication, e.g. [35] [36]), or they extract features (e.g. fast Fourier transform or Wavelet coefficients) from the captured data to train the classifier and perform…”
MethodContinuous mobile authentication using touchscreen gestures
Feng, T., Liu, Z., Kwon, K.-A., Shi, W., Carbunar, B., Jiang, Y., & Nguyen, N. (2012) · 2012 IEEE Conference on Technologies for Homeland Security (HST) · doi:10.1109/ths.2012.6459891 · Cited by 308
Deep Learning-Based Gait Recognition Using Smartphones in the Wild
Zou, Q., Wang, Y., Wang, Q., Zhao, Y., & Li, Q. (2020) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2020.2985628 · Cited by 305
(2019) · ACM Computing Surveys · doi:10.1145/3230633 · Cited by 303
Surveying the Development of Biometric User Authentication on Mobile Phones
Meng, W., Wong, D. S., Furnell, S., & Zhou, J. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2014.2386915 · Cited by 300
Metadata
- Authors
- Mantyjarvi, J., Lindholm, M., Vildjiounaite, E., Makela, S., & Ailisto, H.
- Venue
- Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.
- Publisher
- IEEE
- Published
- 2006-10-11
- Volume
- 2
- Pages
- 973-976
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W2151373013
- Cited by
- 408
- References
- 0
- FWCI
- 29.01
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Mantyjarvi, J., Lindholm, M., Vildjiounaite, E., Makela, S., & Ailisto, H. (2006). Identifying Users of Portable Devices from Gait Pattern with Accelerometers. Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005. https://doi.org/10.1109/icassp.2005.1415569
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