TITLE: Comparing Markerless And Marker-Based Motion Capture Systems For Clinical Motion Analysis Of Children And Youth With Atypical Lower Limb Mobility
INSTRUCTORS: Tim Bhatnagar1,2, Mona Behrouzian1, and Alec Black1
1 The Motion Lab, Sunny Hill Health Centre at BC Children’s Hospital, Vancouver, Canada
2 Department of Orthopaedics, University of British Columbia, Vancouver, Canada
E-mail: tbhatnagar@cw.bc.ca
PURPOSE: The purpose of this tutorial is for attendees to learn about pros and cons of markerless motion capture approaches (specifically, Theia3D), with particular focus on the discrepancies between markerless and marker-based approaches.
INTENDED AUDIENCE: This tutorial is intended for anyone utilizing, or considering utilizing motion capture for clinical motion analysis in the pediatric population; this may include engineers, kinesiologists, physiotherapists, occupational therapists, prostheticians and orthotists, physiatrists and orthopedic surgeons.
PREREQUISITE KNOWLEDGE: This tutorial will utilize typical kinematic representations of gait and clinical motion in graphical format. Familiarity with these graphical representations of motion as well as the underlying theory that covers segment coordinate systems and calculation of joint angles, is recommended.
COURSE OUTLINE:
Introduction: Gait and clinical motion analysis has traditionally relied on marker-based motion capture systems to collect data, including kinematics. However, limitations associated with the placement of the markers – including accurate placement of anatomical markers and repeatability between operators – have been well recognized by researchers in this field for some time. Furthermore, the amount of hardware required for capturing marker-based data, the amount of time required to affix and remove markers, and the effect that marker placement has on the ability to capture ‘unencumbered’ motion data, are all limitations that are currently accepted as necessary [1]. Markerless motion analysis systems are becoming more and more popular, and have already been concurrently compared, and presented as a potential reasonable alternative, to marker-based systems for clinical motion analysis in specific patient populations [2]. Gait and Clinical Motion laboratories are often focused towards pediatric biomechanics, thus, there is an opportunity for further evaluation of novel markerless motion analysis systems in pediatric populations involving: those with atypical gait, those who use walking aids, and those recovering from interventions and/or injury.
While previous work by Kanko et al. have quantified comparisons between marker-based and markerless systems [2], the inherent functioning of the pose estimation algorithms, utilizing machine learning algorithms, of the Theia3D markerless system has the potential to perform differently in cases where the subject in the video exhibits atypical anatomy or physiological motion (e.g. gait, sporting maneuvers, etc.). We intend to survey how well marker-based and markerless system analyses perform across a variety of patients we see in our lab. Our aim will be to identify characteristics – anatomical, mobility-aid and motion-based – that affect the performance of the markerless system.
Clinical Significance: Changing the way motion analysis data are collected, without markers, could have a significant role to play in moving the field of motion capture forward. There is potential for a systemic change in clinical resource use, patient/family time required and overall quality of experience.
Methods: At The Motion Lab, Sunny Hill Health Centre at BC Children’s Hospital (TML), we have been capturing and analyzing gait and clinical motion trials with both a Qualisys marker-based system (Qualisys, Göteborg, Sweden) and a Theia3D markerless system (Theia Markerless Inc., Kingston, Canada). We have established a routine process in which to collect, analyze and compare (using Visual3D) gait and clinical motion data of our patients.
Demonstration: In this session, we intend to demonstrate our process for collecting and analyzing data, so attendees can get a sense of what processes are involved with using two systems simultaneously, but with specific focus on the utilization of a Theis3D markerless system. We also will be presenting a variety of case data (example: Figure 1) to facilitate discussion regarding when the two system analyses agree, and when they do not.
Figure 1 – Kinematic comparison data (n=1) between marker-based (RED) and markerless (GREEN) analysis. Sagittal, coronal and transverse kinematics are in the left, center and right columns, respectively.
Summary: Markerless motion capture systems are garnering a lot of attention for biomechanical analysis purposes. In this session, we intend to demonstrate our simultaneous use of a marker-based and markerless system to collect gait and clinical motion data from pediatric patients. We will also discuss discrepancies in the analyses from each system, with reference to distinguishable features of the patients.
References:
1. Kanko R.M. et al. (2021) J Biomech, 121:110422. doi: 10.1016/j.jbiomech.2021.110422 .
2. Kanko R.M. et al. (2021) J Biomech, 127:110665. doi: 10.1016/j.jbiomech.2021.110665 .
The authors have no conflicts of interest to disclose.