research-article

Continuous Identification in Smart Environments Using Wrist-Worn Inertial Sensors

Authors:

Alejandro S. Guinea,

Andrey Boytsov,

Ludovic Mouline,

Yves Le TraonAuthors Info & Claims

MobiQuitous '18: Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Pages 87 - 96

https://doi.org/10.1145/3286978.3287001

Published: 05 November 2018 Publication History

Abstract

In this paper, we propose a new approach capable of performing continuous identification of users in home and office environments based on hand and arm motion patterns obtained from a wrist-worn inertial measurement unit (IMU). Different from state-of-the-art methods, our approach is not constrained to particular types of movements, gestures, or activities, thus allowing users to perform freely and unconstrained their daily routines while the identification takes place. We evaluate our approach by conducting an in the lab study and two in-situ studies, one in home environment and one in office environment. Our studies involved a total of 29 different participants and the data collected corresponds to approximately 256 hours. The results obtained in the studies indicate that our approach is able to perform continuous user identification with an accuracy of 0.88 for office environments and 0.71 for the average size of a household.

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Cited By

Sanchez Guinea AHeinrich SMühlhäuser M(2022)Activity-Free User Identification Using Wearables Based on Vision TechniquesSensors10.3390/s2219736822:19(7368)Online publication date: 28-Sep-2022
https://doi.org/10.3390/s22197368
Xin JPhoha VSalekin A(2022)Combating False Data Injection Attacks on Human-Centric Sensing ApplicationsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35345776:2(1-22)Online publication date: 7-Jul-2022
https://dl.acm.org/doi/10.1145/3534577
Vatavu RSchipor O(2022)Formalizing Digital Proprioception for Devices, Environments, and UsersAmbient Intelligence – Software and Applications – 12th International Symposium on Ambient Intelligence10.1007/978-3-031-06894-2_1(1-10)Online publication date: 1-Sep-2022
https://doi.org/10.1007/978-3-031-06894-2_1
Show More Cited By

Index Terms

Continuous Identification in Smart Environments Using Wrist-Worn Inertial Sensors
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Empirical studies in ubiquitous and mobile computing
    2. Ubiquitous and mobile computing systems and tools

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MobiQuitous '18: Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

November 2018

490 pages

ISBN:9781450360937

DOI:10.1145/3286978

General Chairs:
Henning Schulzrinne
Columbia University, USA
,
Pan Li
Case Western Reserve University, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 November 2018

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MobiQuitous '18

MobiQuitous '18: Computing, Networking and Services

November 5 - 7, 2018

NY, New York, USA

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Overall Acceptance Rate 26 of 87 submissions, 30%

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Cited By

Sanchez Guinea AHeinrich SMühlhäuser M(2022)Activity-Free User Identification Using Wearables Based on Vision TechniquesSensors10.3390/s2219736822:19(7368)Online publication date: 28-Sep-2022
https://doi.org/10.3390/s22197368
Xin JPhoha VSalekin A(2022)Combating False Data Injection Attacks on Human-Centric Sensing ApplicationsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35345776:2(1-22)Online publication date: 7-Jul-2022
https://dl.acm.org/doi/10.1145/3534577
Vatavu RSchipor O(2022)Formalizing Digital Proprioception for Devices, Environments, and UsersAmbient Intelligence – Software and Applications – 12th International Symposium on Ambient Intelligence10.1007/978-3-031-06894-2_1(1-10)Online publication date: 1-Sep-2022
https://doi.org/10.1007/978-3-031-06894-2_1
Ali Shah SShaghaghi AKanhere SZhang JAnwar ADoss R(2020)Echo-ID: Smart User Identification Leveraging Inaudible Sound SignalsIEEE Access10.1109/ACCESS.2020.30318998(194508-194522)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3031899
Aldeer MOrtiz JHoward RMartin RPoor VHan Z(2019)PatientSenseProceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3360774.3360796(143-152)Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1145/3360774.3360796
Huang AWang DZhao RZhang Q(2019)Au-IdProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33289193:2(1-26)Online publication date: 21-Jun-2019
https://dl.acm.org/doi/10.1145/3328919
Ganegoda HJovanov E(2019)IoT Based Longitudinal Monitoring of Activity and Posture Transitions in Smart Homes2019 SoutheastCon10.1109/SoutheastCon42311.2019.9020328(1-4)Online publication date: Apr-2019
https://doi.org/10.1109/SoutheastCon42311.2019.9020328
Shah SKanhere S(2019)Recent Trends in User Authentication – A SurveyIEEE Access10.1109/ACCESS.2019.29324007(112505-112519)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2932400

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