Machine-learning-based validation of Microsoft Azure Kinect in measuring gait profiles

The dataset was used to validate Microsoft Azure Kinect in measuring gait profiles, employing machine learning techniques to investigate the impact of residual errors due to environmental, methodological, and processing factors on the accuracy of gait profile assessments. Data were collected from healthy and post-stroke subjects using a motion capture system and a 3D camera-based system with MAK, and corresponding gait profiles were estimated and compiled into a dataset. The estimated gait profiles include spatiotemporal, asymmetry, and body center of mass parameters to capture various normal and pathological gait characteristics. Contact e-mail: [e-mail] (Claudia Ferraris) [e-mail] (Luca Vismara) [e-mail] (Veronica Cimolin)