Identifying users of portable devices from gait pattern with accelerometers

Jani Mäntyjärvi; Mikko Lindholm; Elena Vildjiounaite; Satu Marja Mäkelä; Heikki Ailisto

doi:10.1109/ICASSP.2005.1415569

Identifying users of portable devices from gait pattern with accelerometers

Jani Mäntyjärvi, Mikko Lindholm, Elena Vildjiounaite, Satu Marja Mäkelä, Heikki Ailisto

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

344 Citations (Scopus)

Abstract

Identifying users of portable devices from gait signal 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. Identifying the users with this novel gait recognition method showed to be possible. Best equal error rate (EER=7%) was achieved with signal correlation method, while frequency domain method and two variations of data distribution statistics method produced EER of 10%, 18% and 19%, respectively.

Original language	English
Title of host publication	2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing
Volume	II
DOIs	https://doi.org/10.1109/ICASSP.2005.1415569
Publication status	Published - 1 Dec 2005
MoE publication type	A4 Article in a conference publication
Event	2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States Duration: 18 Mar 2005 → 23 Mar 2005

Publication series

Series	Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
ISSN	1520-6149

Conference

Conference	2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/Territory	United States
City	Philadelphia, PA
Period	18/03/05 → 23/03/05

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10.1109/ICASSP.2005.1415569

https://publications.vtt.fi/julkaisut/muut/2005/ICASSP05.pdf

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Mäntyjärvi, J., Lindholm, M., Vildjiounaite, E., Mäkelä, S. M., & Ailisto, H. (2005). Identifying users of portable devices from gait pattern with accelerometers. In 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing (Vol. II). [1415569] Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing https://doi.org/10.1109/ICASSP.2005.1415569

Mäntyjärvi, Jani ; Lindholm, Mikko ; Vildjiounaite, Elena et al. / Identifying users of portable devices from gait pattern with accelerometers. 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing. Vol. II 2005. (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing).

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title = "Identifying users of portable devices from gait pattern with accelerometers",

abstract = "Identifying users of portable devices from gait signal 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. Identifying the users with this novel gait recognition method showed to be possible. Best equal error rate (EER=7%) was achieved with signal correlation method, while frequency domain method and two variations of data distribution statistics method produced EER of 10%, 18% and 19%, respectively.",

author = "Jani M{\"a}ntyj{\"a}rvi and Mikko Lindholm and Elena Vildjiounaite and M{\"a}kel{\"a}, {Satu Marja} and Heikki Ailisto",

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booktitle = "2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing",

note = "2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 ; Conference date: 18-03-2005 Through 23-03-2005",

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Mäntyjärvi, J , Lindholm, M , Vildjiounaite, E , Mäkelä, SM & Ailisto, H 2005, Identifying users of portable devices from gait pattern with accelerometers. in 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing. vol. II, 1415569, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05, Philadelphia, PA, United States, 18/03/05. https://doi.org/10.1109/ICASSP.2005.1415569

Identifying users of portable devices from gait pattern with accelerometers. / Mäntyjärvi, Jani ; Lindholm, Mikko ; Vildjiounaite, Elena et al.

2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing. Vol. II 2005. 1415569 (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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Mäntyjärvi J , Lindholm M , Vildjiounaite E , Mäkelä SM , Ailisto H. Identifying users of portable devices from gait pattern with accelerometers. In 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing. Vol. II. 2005. 1415569. (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). doi: 10.1109/ICASSP.2005.1415569

Identifying users of portable devices from gait pattern with accelerometers

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