Measurement and Visualisation of Body Midline Using Sensor Technology - Enhancing Postural Assessment Accuracy with Kinect V2: An Evaluation of Objectivity and Clinical Application

Abstract

Abstract Poor posture has been a prevalent problem which can often lead to chronic pain, musculoskeletal disorders, and a decreased quality of life. Generally, physiotherapists rely on traditional visual inspection methods to assess posture, which can be subjective and inconsistent, making accurate diagnosis and effective treatment challenging. This thesis explores the feasibility and effectiveness of using the Microsoft Kinect V2 sensor and its motion-tracking algorithm for estimating human body posture. The study demonstrates that the Kinect V2 sensor can significantly enhance the accuracy of postural evaluations by delivering numerical measurements and real-time tracking of skeletal movements. This technology reduces observer bias and the variability associated with conventional visual assessments, allowing for detailed angle measurements that can capture subtle deviations in posture. Despite its advantages, the Kinect V2 sensor has limitations, including challenges in tracking all body joints and potential data inaccuracies due to occlusion and effects of wearing footwear. Therefore, it is recommended that Kinect technology be utilized alongside traditional assessment methods to maximize diagnostic accuracy.