A Survey on Ai-Powered Exercise Posture Correction System
Proper exercise posture is essential for preventing injuries and maximizing workout effectiveness, but many individuals lack access to professional trainers. AI-powered exercise posture correction systems provide an affordable and accessible alternative, using tools like Convolutional Neural Networks (CNNs) and pose estimation frameworks such as MediaPipe, OpenPose, PoseNet, and MoveNet. These systems analyze body movements in real time, detect misalignments, and offer immediate feedback to help users improve their form. This paper reviews the technologies, methods, and applications of these systems in fitness, rehabilitation, and elderly care. It highlights their benefits, challenges, and potential for making exercise guidance more widely available and effective
Authors
- Aiswarya Rajendran (ORCID: https://orcid.org/0000-0003-4712-9955)
- Abdul K. Siraj (ORCID: https://orcid.org/0000-0003-2162-6857)
- Praveen Kumar S (ORCID: https://orcid.org/0000-0002-9002-7658)
- Mehul Shah (ORCID: https://orcid.org/0000-0002-0720-7632)
- Subhasis Das (ORCID: https://orcid.org/0000-0002-6163-9583)
Institutions
- Klinik und Poliklinik für Psychosomatik und Psychotherapie (DE)
Publication Details
- Journal
- International Journal of Advances in Engineering and Management
- Published
- 2024-12-01
- DOI
- https://doi.org/10.35629/5252-0612120124
- Citations
- 2
- Primary Topic
- Ergonomics and Musculoskeletal Disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.29