Personal Home Fitness System Based on Computer Vision

The Personal Home Fitness System is an innovative approach in the realm of home fitness technology, integrating a dataset based on Long Short-Term Memory (LSTM) and YoloV7 human recognition to facilitate precise fitness training. This system distinguishes movements into “standard" and “non-standard" categories, thereby enhancing the personalized training experience. A pivotal feature of its design is the YoloV7 system, capable of accurately identifying the amplitude of movements, which is essential for effective fitness activities. Our results display the system’s high accuracy and low loss metrics, indicating its efficiency and reliability. This research marks a significant advancement in combining artificial intelligence with physical fitness, providing an advanced solution for home fitness enthusiasts and establishing a new direction in the integration of machine learning with exercise technology.