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Motion analysis of the JHU-ISI Gesture and Skill Assessment Working Set using Robotics Video and Motion Assessment Software

Purpose The JIGSAWS dataset is a fixed dataset of robot-assisted surgery kinematic data used to develop predictive models of skill. The purpose of this study is to analyze the relationships of self-defined skill level with global rating scale scores and kinematic data (time, path length and movement...

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Bibliographic Details
Published in:International journal for computer assisted radiology and surgery 2020-12, Vol.15 (12), p.2017-2025
Main Authors: Lefor, Alan Kawarai, Harada, Kanako, Dosis, Aristotelis, Mitsuishi, Mamoru
Format: Article
Language:English
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Summary:Purpose The JIGSAWS dataset is a fixed dataset of robot-assisted surgery kinematic data used to develop predictive models of skill. The purpose of this study is to analyze the relationships of self-defined skill level with global rating scale scores and kinematic data (time, path length and movements) from three exercises (suturing, knot-tying and needle passing) (right and left hands) in the JIGSAWS dataset. Methods Global rating scale scores are reported in the JIGSAWS dataset and kinematic data were calculated using ROVIMAS software. Self-defined skill levels are in the dataset (novice, intermediate, expert). Correlation coefficients (global rating scale-skill level and global rating scale-kinematic parameters) were calculated. Kinematic parameters were compared among skill levels. Results Global rating scale scores correlated with skill in the knot-tying exercise ( r  = 0.55, p  = 0.0005). In the suturing exercise, time, path length (left) and movements (left) were significantly different ( p 
ISSN:1861-6410
1861-6429
DOI:10.1007/s11548-020-02259-z