## 4 Discussion
Given that the model can predict angles when motion is not planar, the requirement for specific camera placement is eliminated. Requiring only a single camera ensures easier deployment outside of laboratory settings, making this an ideal candidate for workplace assessments. In addition, these results can help to push the field of markerless motion capture forward and increase the potential applications of using open-source methods. The methods described in this paper have limitations. While the ultimate goal is to achieve a fully markerless system that requires a single camera, the limitation of using markers was necessary for validation against a gold-standard motion capture system. Comparison against an OMC has been seen in previous work as an effective way to assess the accuracy of an MMC while the participants still have markers present [16]. One of the main goals of this research is to provide a foundation for future research in the development of markerless motion capture systems to monitor wrist kinematics. As the feature importance value of the elbow markers is low across all models, it appears the elbow marker is less important than markers on the wrist and hand. There is a possibility that similar results could be achieved if the elbow markers were removed or not included. This would push the methodology closer towards the end goal of MMC for wrist kinematics. Future work could involve further validation of methods applied in this paper by virtually removing the markers through the application of advanced image editing techniques. Another limitation is that subjects had a very clear and simplistic set of FE and RUD movements to complete. This was required to provide a clear idea of how well the methodology worked across subjects. If an alternative task was used that allowed subjects to move their upper limbs in a non-structured manner, it would be difficult to discern if inaccuracies in the model were subject-specific, task-specific, or if there was an overall inaccuracy. Future work could evaluate the accuracy of the various methods outlined in this paper while subjects complete simulated workplace tasks. Due to the nature of the experiment, the ability to generalize may be limited to the laboratory, as performance in settings outside of these confines may be inadequate. Additionally, as the population was selected based on convenience, there may be a limitation on how well the model may perform on a more diverse set of participants. Overall, we have shown the ability to predict wrist angles with input from off-the-shelf, reasonably inexpensive cameras coupled with open-source algorithms confirms the potential to make MMC more accessible and available. Conceptualization, J.C., M.L.O., and K.D.G. ; methodology, J.C.; software, J.C.; validation, J.C.; formal analysis, J.C.; investigation, J.C.; resources, M.L.O. and K.D.G. ; data curation, J.C.; writing--original draft preparation, J.C.; writing--review and editing, M.L.O., K.D.G., and A.H.-W.; visualization, J.C.; supervision, M.L.O., A.H.-W., C.Y., and K.D.G. ; project administration, J.C. All authors have read and agreed to the published version of the manuscript. This research was funded by the Natural Sciences and Engineering Research Council of Canada, grant numbers RGPIN-2019-05240 and RGPIN-2019-05009. This study was conducted in accordance with the Declaration of Helsinki and approved by the University of Guelph Research Ethics Board (REB #22-05-004). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.