This technology leverages artificial intelligence (AI) and motion capture to analyze and predict human movement patterns. Using video-based tracking and sensor data, it creates a personalized digital model of an individual’s biomechanics in different movements (e.g. sitting, walking, squatting, other functional movements, etc.). This model can simulate how a person moves in different environments or under various conditions, such as fatigue or injury, to optimize performance and prevent injuries. The system is designed for applications in rehabilitation, sports, occupational safety, and military training, providing real-time insights into movement efficiency and potential risk factors. Background: Human movement analysis is critical in fields like physical therapy, sports training, and workplace safety, yet existing methods rely on expensive motion capture systems or subjective assessments. Current solutions often lack real-time adaptability and fail to account for individual variations in biomechanics. This technology offers a cost-effective, AI-driven alternative that provides detailed motion predictions without requiring complex or invasive equipment. By using generative AI, it can simulate movements in different scenarios, improving injury prevention and rehabilitation strategies. Applications:
Advantages: