Novel AI system could pave way for more effective digital coaching, rehab tools

A novel AI system capable of recognizing yoga poses with high accuracy could pave the way for more effective digital coaching tools, rehab platforms and movement-monitoring applications.

A new study, co-authored by the University of East London (UEL), analysed four novel AI models and their ability to identify yoga poses; the researchers found that their best-performing model, Hierarchichal CoAtNet 1, achieved accuracy levels of over 93% during testing, significantly outperforming previous models. 

This research shows how AI can be used to make movement-based coaching and rehabilitation more accessible. By recognising yoga poses with a high degree of accuracy and providing feedback in real time, these systems could help support people who cannot easily access in-person instruction, whether because of their location, mobility challenges or cost. It demonstrates the potential for AI, computer vision and robotics to expand access to health and wellbeing tools for a wider range of people." 

Dr. Laura Vanderbloemen, Senior Lecturer at UEL and co-author of the study

The AI model incorporates in its learning the natural hierarchical relationships between yoga poses, so, rather than treating each pose as an isolated category, the AI model identifies broader pose families, before learning about specific variations, similarly as to how humans understand and categorise movement. 

This system could have practical applications in the real-world and deliver feedback in real time, as the model processed images in approximately 16 to 17 milliseconds per batch under testing conditions and achieved real-time speeds of around 65 to 70 frames per second during streaming inference. 

The researchers believe this model could support a wide range of applications that require accurate monitoring of physical activity, along with providing feedback that yoga instructors, physios and healthcare professionals could use to better understand posture quality and movement patterns and improve personalised coaching and rehabilitation. 

The research was a collaborative effort involving researchers from the University of East London, Nirma University, Imperial College London and Doctor On Click, bringing together expertise in artificial intelligence, computer vision, digital health and movement science.