Video and Accelerometer-Based Motion Analysis for Automated Surgical Skills Assessment

02/24/2017
by   Aneeq Zia, et al.
0

Purpose: Basic surgical skills of suturing and knot tying are an essential part of medical training. Having an automated system for surgical skills assessment could help save experts time and improve training efficiency. There have been some recent attempts at automated surgical skills assessment using either video analysis or acceleration data. In this paper, we present a novel approach for automated assessment of OSATS based surgical skills and provide an analysis of different features on multi-modal data (video and accelerometer data). Methods: We conduct the largest study, to the best of our knowledge, for basic surgical skills assessment on a dataset that contained video and accelerometer data for suturing and knot-tying tasks. We introduce "entropy based" features - Approximate Entropy (ApEn) and Cross-Approximate Entropy (XApEn), which quantify the amount of predictability and regularity of fluctuations in time-series data. The proposed features are compared to existing methods of Sequential Motion Texture (SMT), Discrete Cosine Transform (DCT) and Discrete Fourier Transform (DFT), for surgical skills assessment. Results: We report average performance of different features across all applicable OSATS criteria for suturing and knot tying tasks. Our analysis shows that the proposed entropy based features out-perform previous state-of-the-art methods using video data. For accelerometer data, our method performs better for suturing only. We also show that fusion of video and acceleration features can improve overall performance with the proposed entropy features achieving highest accuracy. Conclusions: Automated surgical skills assessment can be achieved with high accuracy using the proposed entropy features. Such a system can significantly improve the efficiency of surgical training in medical schools and teaching hospitals.

READ FULL TEXT
research
12/22/2017

Automated Surgical Skill Assessment in RMIS Training

Purpose: Manual feedback in basic RMIS training can consume a significan...
research
07/16/2020

Neuro-Endo-Trainer-Online Assessment System (NET-OAS) for Neuro-Endoscopic Skills Training

Neuro-endoscopy is a challenging minimally invasive neurosurgery that re...
research
08/27/2020

Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field

Surgical skill assessment is important for surgery training and quality ...
research
07/05/2022

Video-based Surgical Skills Assessment using Long term Tool Tracking

Mastering the technical skills required to perform surgery is an extreme...
research
06/13/2018

Higher Order of Motion Magnification for Vessel Localisation in Surgical Video

Locating vessels during surgery is critical for avoiding inadvertent dam...
research
03/03/2021

Deep Neural Networks for the Assessment of Surgical Skills: A Systematic Review

Surgical training in medical school residency programs has followed the ...
research
08/04/2022

Surgical Skill Assessment via Video Semantic Aggregation

Automated video-based assessment of surgical skills is a promising task ...

Please sign up or login with your details

Forgot password? Click here to reset