Gym Posture Recognition and Feedback Generation Using Mediapipe and OpenCV

Computer Engineering

Everyone benefits from exercise and physical activity. Staying active can benefit you in a variety of ways, regardless of your health or physical abilities. In reality, research shows that “taking it easy” is dangerous. Exercises are often practiced in training centers, through personal tutors, and may also be learned on one’s own with the help of the recorded clips, etc. In fast-paced lifestyles, many people prefer self-learning because the above-mentioned resources might not be available all the time. But in self-learning, one may not find an incorrect pose. One's health might suffer from improper posture, which can cause both short-term acute discomfort and long-term chronic problems. We investigated many applications that can be implemented using data provided by a pre-trained posture estimation model called MediaPipe. Applications include motion capture, gait analysis, sign language detection etc. Building a gym posture monitoring system, which analyses and tracks user motions and postures for faults, is the major goal of this project. The user is then notified of his/her error in the posture through a display screen or a wireless speaker. The inaccurate body pose of the user can be pointed out in real-time so that the user can rectify his/her mistakes.

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