A marker-less human motion analysis system for motion-based biomarker identification and quantification in knee disorders

Kai Armstrong1*, Lei Zhang1, Yan Wen1, Alexander P. Willmott2, Paul Lee2,3 and Xujiong Ye1*

1 Laboratory of Vision Engineering, School of Computer Science, University of Lincoln, Lincoln, United Kingdom
2 School of Sport and Exercise Science, University of Lincoln, Lincoln, United Kingdom
3 MSK Doctors, Sleaford, United Kingdom

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This study has not only demonstrated the effectiveness of utilising motion-based biomarkers for quantifying movement but has also established a robust foundation for conducting objective MSK analyses. The techniques presented offer a promising avenue for implementing a standardised method of MSK analysis, achievable with any standard camera, even a mobile phone. This accessibility opens doors for remote disease monitoring, enabling the early identification of pre-disease stages.

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