(Georgia Institute of Technology, 2015)
Zia, Aneeq; Sharma, Yachna; Bettadapura, Vinay; Sarin, Eric L.; Clements, Mark A.; Essa, Irfan
We present an automated framework for visual assessment
of the expertise level of surgeons using the OSATS (Objective Structured Assessment of Technical Skills) criteria. Video analysis techniques
for extracting motion quality via frequency coefficients are introduced.
The framework is tested on videos of medical students with different expertise levels performing basic surgical tasks in a surgical training lab setting. We demonstrate that transforming the sequential time data into
frequency components effectively extracts the useful information differentiating between different skill levels of the surgeons. The results show significant performance improvements using DFT and DCT coefficients
over known state-of-the-art techniques.