Background: This research presents a pioneering and comprehensive approach aimed at delivering personalized exercise and yoga support to the senior population. The primary objective of this research is to enhance physical well-being, boost engagement, foster adherence to exercise and yoga routines, and refine users' posture and balance. Methods: A pivotal phase in this project involves keypoint extraction, skillfully executed using MoveNet, an advanced posture estimation model. To achieve this, deep learning algorithms like Convolutional Neural Networks, Dense Neural Networks, and Multi-Layer Perceptrons are deployed to effectively classify and categorize yoga and exercise positions.
Results:The culmination of this endeavor manifests in the form of an interactive web application. The robustness and efficacy of the system are underscored by extensive user testing, which has also assessed its usability and potential to significantly enhance the physical well-being of the elderly. In summation, this research represents a substantial advancement in the realm of targeted exercise and yoga support, expressly designed to cater to the distinctive needs of the senior demographic.
Conclusion:Concluding research stands as a testament to the potential of technology in promoting physical well-being and enhancing the lives of the elderly through tailored exercise and yoga support systems.Trial Registration: User testing phase carried out in retrospectively registered manner.