Automated Pilates Ring Tracking and Motion Analysis

With the increase in sedentary lifestyle and increasing stress level, Pilates has become more popular due to its emphasis on alignment, controlled movements, and breathing. However, traditional Pilates exercises have limitations, such as restricted movement ranges, insufficient resistance, and difficulty in targeting specific muscle groups. To address these issues, the Pilates ring is integrated into work routines. The Pilates ring is a versatile piece of exercise equipment that allows users to isolate and target specific muscle groups, promoting enhanced strength and muscle activation. To overcome the challenges associated with using motion analysis sensors in the Pilates ring, we adopt computer vision methods, leveraging libraries like OpenCV and MediaPipe. Computer vision enables motion detection and analy-sis of visual information, facilitating the tracking and monitoring of exercise performance. Through qualitative assessments, we analyse patient movements and evaluate posture accuracy by measuring the range of motion of the Pilates ring using computer vision tools. This research lays the foundation for a robust model applicable in both home and gym settings, augmenting the effectiveness of Pilates exercises. Future endeavours involve developing a quantitative assessment of the Pilates ring by measuring the pressure exerted by patients during exercises. By harnessing computer vision, this research aims to offer an accessible and convenient alternative to traditional physiotherapy, empowering individuals to engage in effective Pilates workouts remotely and at their convenience.