Motion sensor data anonymization by time-frequency filtering

Noëlie Debs, Théo Jourdan, Ali Moukadem, Antoine Boutet, Carole Frindel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


Recent advances in wireless actimetry sensors allow recognizing human real-time activities with mobile devices. Although the analysis of data generated by these devices can have many benefits for healthcare, these data also contains private information about users without their awareness and may even cause their re-identification. In this paper, we propose a privacy-preserving framework for activity recognition. The method consists of a two-step process. First, acceleration signals are encoded in the time-frequency domain by three different linear transforms. Second, we propose a method to anonymize the acceleration signals by filtering in the time-frequency domain. Finally, we evaluate our approach for the three different linear transforms with a neural network classifier by comparing the performances for activity versus identity recognition. We extensively study the validity of our framework with a reference dataset: results show an accurate activity recognition (85%) while limiting the re-identifation rate (32%). This represents a large utility improvement (19%) against a slight privacy decrease (10%) compared to state-of-the-art baseline.

Original languageEnglish
Title of host publication28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Number of pages5
ISBN (Electronic)9789082797053
Publication statusPublished - 2021 Jan 24
Event28th European Signal Processing Conference, EUSIPCO 2020 - Amsterdam, Netherlands
Duration: 2020 Aug 242020 Aug 28

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491


Conference28th European Signal Processing Conference, EUSIPCO 2020


  • Activity Recognition
  • Classification
  • Convolutional Neural Networks
  • Privacy
  • Time-Frequency


Dive into the research topics of 'Motion sensor data anonymization by time-frequency filtering'. Together they form a unique fingerprint.

Cite this