HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

User Recognition Based on Daily Actigraphy Patterns

Abstract : The use of inertial sensors such as accelerometers and gyroscopes, which are now often embedded in many wearable devices, has gained attention for their applicability in user authentication applications as an alternative to PINs, passwords, biometric signatures, etc. Previous works have shown that it is possible to authenticate users based on fine-grained kinematic behavior profiles like gait, hand gestures and physical activities. In this work we explore the use of actigraphy data for user recognition based on daily patterns as opposed to fine-grained motion. One of the advantages of the former, is that it does not require to perform specific movements, thus, easing the training and calibration stages. In this work we extracted daily patterns from an actigraphy device and used a random forest classifier and a majority voting approach to perform the user classification. We used a public available dataset collected by 55 participants and we achived a true positive rate of 0.64, a true negative rate of 0.99 and a balanced accuracy of 0.81.
Document type :
Conference papers
Complete list of metadata

https://hal.inria.fr/hal-03182611
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Friday, March 26, 2021 - 2:33:30 PM
Last modification on : Friday, March 26, 2021 - 2:39:09 PM
Long-term archiving on: : Sunday, June 27, 2021 - 6:48:05 PM

File

491176_1_En_6_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Enrique Garcia-Ceja, Brice Morin. User Recognition Based on Daily Actigraphy Patterns. 13th IFIP International Conference on Trust Management (IFIPTM), Jul 2019, Copenhagen, Denmark. pp.73-80, ⟨10.1007/978-3-030-33716-2_6⟩. ⟨hal-03182611⟩

Share

Metrics

Record views

21

Files downloads

2