Motion analysis of the JHU–ISI Gesture and Skill Assessment Working Set II: learning curve analysis

Purpose The Johns Hopkins–Intuitive Gesture and Skill Assessment Working Set (JIGSAWS) dataset is used to develop robotic surgery skill assessment tools, but there has been no detailed analysis of this dataset. The aim of this study is to perform a learning curve analysis of the existing JIGSAWS dat...

Full description

Saved in:
Bibliographic Details
Published in:International journal for computer assisted radiology and surgery 2021-04, Vol.16 (4), p.589-595
Main Authors: Lefor, Alan Kawarai, Harada, Kanako, Dosis, Aristotelis, Mitsuishi, Mamoru
Format: Article
Language:English
Subjects:
Computer Imaging
Computer Science
Datasets
Health Informatics
Imaging
Kinematics
Learning curves
Medicine
Medicine & Public Health
Original Article
Parameters
Pattern Recognition and Graphics
Qualitative analysis
Radiology
Robotic surgery
Surgery
Sutures
Vision
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Purpose The Johns Hopkins–Intuitive Gesture and Skill Assessment Working Set (JIGSAWS) dataset is used to develop robotic surgery skill assessment tools, but there has been no detailed analysis of this dataset. The aim of this study is to perform a learning curve analysis of the existing JIGSAWS dataset. Methods Five trials were performed in JIGSAWS by eight participants (four novices, two intermediates and two experts) for three exercises (suturing, knot-tying and needle passing). Global Rating Scores and time, path length and movements were analyzed quantitatively and qualitatively by graphical analysis. Results There are no significant differences in Global Rating Scale scores over time. Time in the suturing exercise and path length in needle passing had significant differences. Other kinematic parameters were not significantly different. Qualitative analysis shows a learning curve only for suturing. Cumulative sum analysis suggests completion of the learning curve for suturing by trial 4. Conclusions The existing JIGSAWS dataset does not show a quantitative learning curve for Global Rating Scale scores, or most kinematic parameters which may be due in part to the limited size of the dataset. Qualitative analysis shows a learning curve for suturing. Cumulative sum analysis suggests completion of the suturing learning curve by trial 4. An expanded dataset is needed to facilitate subset analyses.
ISSN:1861-6410
1861-6429
DOI:10.1007/s11548-021-02339-8