Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy

Alexander Rind, Djordje Slijepcevic, Matthias Zeppelzauer, Fabian Unglaube, Andreas Kranzl, Brian Horsak

View presentation:2022-10-16T14:10:00ZGMT-0600Change your timezone on the schedule page
Exemplar figure, described by caption below
Clinical gait analysis utilizes 3D motion tracking to record complex time series datasets of patients while they are walking in a gait laboratory. gaitXplorer is a visual analytics approach that classifies cerebral palsy-related gait patterns using a CNN, generates relevance scores using Grad-CAM, and presents the data, the predicted class, and the relevance scores in a visual interface. This case study investigates how clinical gait analysts trust the automated classifications and explanations presented by gaitXplorer.

The live footage of the talk, including the Q&A, can be viewed on the session page, TREX: Session 1.