%Aigaion2 BibTeX export van HES SO Valais Publications
%Saturday 02 May 2026 08:22:09 PM

@ARTICLE{,
    author = {Mart{\'{\i}}nez-Zarzuela, Mario and Gonz{\'{a}}lez-Alonso, Javier and Ant{\'{o}}n-Rodr{\'{\i}}guez, M{\'{\i}}riam and D{\'{\i}}az-Pernas, Francisco J and M{\"{u}}ller, Henning and Simon-Martinez, Cristina},
     month = sep,
     title = {Multimodal video and IMU kinematic dataset on daily life activities using affordable devices},
   journal = {Scientific Data},
      year = {2023},
       doi = {10.1038/s41597-023-02554-9},
  crossref = {10.5281/zenodo.7681317},
  abstract = {Human activity recognition and clinical biomechanics are challenging problems in physical telerehabilitation medicine. However, most
publicly available datasets on human body movements cannot be used to study both problems in an out-of-the-lab movement acquisition
setting. The objective of the VIDIMU dataset is to pave the way towards affordable patient gross motor tracking solutions for daily life
activities recognition and kinematic analysis. The dataset includes 13 activities registered using a commodity camera and five inertial
sensors. The video recordings were acquired in 54 subjects, of which 16 also had simultaneous recordings of inertial sensors. The novelty
of VIDIMU lies in: i) the clinical relevance of the chosen movements, ii) the combined utilization of affordable video and custom sensors,
and iii) the implementation of state-of-the-art tools for multimodal data processing of 3D body pose tracking and motion reconstruction in a
musculoskeletal model from inertial data. The validation confirms that a minimally disturbing acquisition protocol, performed according to
real-life conditions can provide a comprehensive picture of human joint angles during daily life activities.}
}