Year: 2024
Type: article
Abstract: 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: Archana Rajendran, Mohammed Anwar Shah, Ashna Siraj, Praveen Kumar S, Dr. Shyama Das
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4405418420