Is Markerless Three-dimensional Motion Analysis a Viable Alternative to Traditional Gait Analysis? (IMAGine Study)

Many children have trouble with walking and frequently trip and fall. To understand the extent of the changes in their walking, but also to inform and evaluate possible interventions to improve their walking, a gait analysis is carried out. Gait analysis is the assessment of how someone walks. It requires the accurate placement of markers on the skin in anatomical locations. The positions of these markers are then measured using infrared cameras and the results are displayed as movement graphs. These graphs are used in clinical decision making. However, this assessment can be time-consuming and uncomfortable for the child, and it may trigger anxiety, leading to an unnatural walking pattern. This style of assessment may also not be suitable for some children who are either very young or have additional sensory needs.

One potential solution to these problems is to use motion capture systems that do not require markers. Instead, these systems use high-resolution video cameras to capture human motion. Artificial intelligence is then used to identify human body features from the video footage and produces movement graphs. Known as markerless motion capture, this emerging approach has been developed over the last few years and has demonstrated promising results compared to the current marker-based method in adults and children.

However, it is not known how well markerless motion capture works for children with gait abnormalities, which is what this study aims to find out. Therefore, fifty children with movement difficulties will walk barefoot over a walkway with and without markers attached, while markerless and marker-based cameras record all trials simultaneously.

This study will then compare the movement graphs created by the markerless and marker-based motion capture systems. The results of this study will also enable Alder Hey to be the lead clinical gait lab user of markerless technology in the UK, helping other gait labs to adopt the technology.