557 citations · 895 across the 11 of their papers we have counts for
5 papers · 1 filter
Paving the Way Towards Kinematic Assessment Using Monocular Video: A Preclinical Benchmark of State-of-the-Art Deep-Learning-Based 3D Human Pose Estimators Against Inertial Sensors in Daily Living Activities
Mario Medrano-Paredes, Carmen Fernández-González, Francisco-Javier Díaz-Pernas +3
Advances in machine learning and wearable sensors offer new opportunities for capturing and analyzing human movement outside specialized laboratories. Accurate assessment of human…
A comparative study on wearables and single-camera video for upper-limb out-of-thelab activity recognition with different deep learning architectures
Mario Martínez-Zarzuela, David González-Ortega, Míriam Antón-Rodríguez +3
The use of a wide range of computer vision solutions, and more recently high-end Inertial Measurement Units (IMU) have become increasingly popular for assessing human physical acti…
Comparative Analysis of Kinect-Based and Oculus-Based Gaze Region Estimation Methods in a Driving Simulator
David González-Ortega, Francisco Javier Díaz-Perna, Mario Martínez-Zarzuela +1
Driver's gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens th…
Multimodal video and IMU kinematic dataset on daily life activities using affordable devices (VIDIMU)
Mario Martínez-Zarzuela, Javier González-Alonso, Míriam Antón-Rodríguez +3
Human activity recognition and clinical biomechanics are challenging problems in physical telerehabilitation medicine. However, most publicly available datasets on human body movem…
Indoor 3D Video Monitoring Using Multiple Kinect Depth-Cameras
M. Martínez-Zarzuela, M. Pedraza-Hueso, F. J. Díaz-Pernas +2
This article describes the design and development of a system for remote indoor 3D monitoring using an undetermined number of Microsoft(R) Kinect sensors. In the proposed client-se…