Determination of shoulder global range of motion

The shoulder joint, which has a great degree of rotation and mobility, is one of the most important joint of the human body. It is crucial in allowing people to do activities of daily living (ADLs) such as drinking water and bathing. Yet, it is one of the joints that is prone to injuries and dysfunction. This research aims to validate the marker-less optical motion capture system to substitute the previous gold standard marker-based optical motion capture system. Six dry- run volunteers with no history of shoulder injuries were selected for this study. The individuals were required to execute 5 ADLs, 8 standard ROMs, 3 global ROMs, and 2 scapular ROMs, all of which were recorded using a marker-based and marker- less optical motion capture system. A new marker-less machine learning system that uses a motion capture system, Precise Marker-less that can precisely find the acromion and body landmarks has been incorporated as part of this study, and it has been shown by the statistical testing- RMSE and Spearman’s ranking correlation coefficient to have a significant correlation with the marker-based system. It has achieved an overall low RMSE value and high Spearman’s coefficient, proving that the accuracy of the marker-less is quite on par with the marker-based system and both are systems strongly correlated. In addition, tasks were modified and a scapular tracking device-digitiser was created, which might greatly enhance the evaluation of scapular range of motion. Further work will aim to monitor the accuracy of the Z-axis of Precise Marker-less, widen the local database, analyse scapular motions and the possibility to incorporate IMU sensors. This ultimately explores towards the possibilities of remote monitoring and algorithmic assessment in determining the need for surgery or rehabilitation, addressing the global issue of shoulder discomfort.Bachelor of Engineering (Mechanical Engineering