Abstract: This comprehensive literature review investigates the efficacy and advancements of form perfectors in correcting posture deviations, leveraging the innovative technologies of OpenCV and MediaPipe. Posture irregularities, prevalent across diverse demographics, significantly impact health and well-being. Form perfectors, encompassing mobile devices and exercise regimens, offer promising solutions for addressing these concerns. However, their effectiveness, mechanisms, and integration into practice necessitate critical evaluation. Employing a systematic approach, this review synthesizes recent research findings, highlighting the multifaceted applications of form perfectors. By integrating OpenCV and MediaPipe technologies, this study extends the traditional review framework, enabling detailed analysis of posture-related data, including skeletal tracking, joint angles, and movement dynamics. Through this lens, the review assesses the effectiveness of form perfectors in mitigating common postural deviations such as kyphosis, lordosis, and forward head posture. Furthermore, the review elucidates the theoretical underpinnings of form perfectors, elucidating biomechanical principles and sensorimotor feedback mechanisms. It explores the integration of OpenCV and MediaPipe within form-perfection frameworks, enabling real-time posture assessment and personalized interventions. Additionally, this review examines the role of machine learning algorithms in optimizing form perfectors' adaptability and efficacy, paving the way for intelligent and personalized posture correction solutions
Keywords: Posture correction, Form perfectors, OpenCV, MediaPipe, Skeletal tracking
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DOI:
10.17148/IJARCCE.2024.13546
