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Marker-less motion capture is a rapidly advancing field that can take simple RGB image sequences, or more advanced Red Green Blue Depth (RGB-D) image sequences obtained using depth sensors, and outputs an estimated human pose. This method of human pose estimation allows for the extraction of biomechanical features which can then be analysed by clinicians to give more insights into a patient’s movement capabilities. When compared to other, more clinically proven technologies such as the Knee Kinesiography (KneeKG), biomechanics presented have the advantage of being more representative of natural movement without the obstructive markers placed on the body. This Significant difference of up to 10° degrees in range of motion for the knee could be the key to better identifying a person’s gait or tracking their natural walking pattern over time, while also being more robust and better suited to a smaller clinical environment. 

Project Team:

Prof. Paul Lee

Medical Director -MSK Doctors 

Prof. Xujiong Ye

Professor of Computer Vision and Medical Imaging - UoL

Dr. Lei Zhang

Senior Lecturer - UoL

Dr. Bethan Whiting

Governance and CQC Manager - MSK Doctors

Mr George Williams

Senior Developer - MSK Doctors

Mr Kai Armstrong

Senior MRI Technician - MSK Doctors 

Ms Emma Bateson

Junior MRI Technician - MSK Doctors

Mrs Hayley Green

Research Admin - MSK Doctors

Other Research Projects:

Knee vMRI
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