RT info:eu-repo/semantics/article
T1 Multimodal video and IMU kinematic dataset on daily life activities using affordable devices
A1 Martínez Zarzuela, Mario
A1 González Alonso, Javier
A1 Antón Rodríguez, Miriam
A1 Díaz Pernas, Francisco Javier
A1 Henning, Müller
A1 Simón Martínez, Cristina
AB 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 dataset 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.
PB Nature
YR 2023
FD 2023-09-22
LK https://uvadoc.uva.es/handle/10324/64478
UL https://uvadoc.uva.es/handle/10324/64478
LA eng
NO Martínez-Zarzuela, M., González-Alonso, J., Antón-Rodríguez, M. et al. Multimodal video and IMU kinematic dataset on daily life activities using affordable devices. Sci Data 10, 648 (2023). https://doi.org/10.1038/s41597-023-02554-9
NO Producción Científica
DS UVaDOC
RD 09-abr-2025