TY - JOUR
T1 - Sensor-free computer-vision hand-motion entropy and video-analysis of technical performance during open surgery on fresh cadavers
T2 - Human Factors and Ergonomics Society 2016 International Annual Meeting, HFES 2016
AU - Mackenzie, Colin F.
AU - Watts, Darcy
AU - Patel, Rajan
AU - Yang, Shiming
AU - Hagegeorge, George
AU - Garofalo, Evan
AU - Hu, Peter F.
AU - Puche, Adam
AU - Shalin, Valerie
AU - Pugh, Kristy
AU - Granite, Guinevere
AU - Stansbury, Lynn G.
AU - Shackelford, Stacy
AU - Tisherman, Samuel
N1 - Publisher Copyright:
Copyright 2016 by Human Factors and Ergonomics Society.
PY - 2016
Y1 - 2016
N2 - Computer vision (CV) hand motion analysis, video-recorded instrument organization and use, and handactivity summarized by Shannon Joint Entropy (variations in seemingly random movements), have potential for unbiased evaluation of surgical technical performance. We hypothesized that Individual Procedure Performance Scores (IPS), as determined by co-located, trained observers, and hand-motion analysis show congruence among operators by levels and types of surgical training and experience. Surgical residents, expert trauma surgeons and anatomists were video-recorded performing axillary artery exposure and control (AA) on fresh cadavers. Color-coded gloves permitted motion-tracking and CV hand motion analysis. Timing and instrument-use metrics were obtained through video reviews. IPS, idle and active times, elapsed time to division of pectoralis minor, type and number of instruments used, and calculated Shannon Joint Entropy values discriminated among the three groups of participants. Experts had lowest entropy values, idle and active times, and shortest time to divide pectoralis minor, using fewer instruments. Residents improved with training, not reaching expert levels, but showed deterioration 12-18 months later. Anatomists' results differed substantially from expert and resident surgeons. Surgeon's IPS scores mirrored the results of hand motion analysis. Conclusions Hand motion analysis techniques, which were congruent with IPS evaluations, can discriminate levels of surgical skill and training.
AB - Computer vision (CV) hand motion analysis, video-recorded instrument organization and use, and handactivity summarized by Shannon Joint Entropy (variations in seemingly random movements), have potential for unbiased evaluation of surgical technical performance. We hypothesized that Individual Procedure Performance Scores (IPS), as determined by co-located, trained observers, and hand-motion analysis show congruence among operators by levels and types of surgical training and experience. Surgical residents, expert trauma surgeons and anatomists were video-recorded performing axillary artery exposure and control (AA) on fresh cadavers. Color-coded gloves permitted motion-tracking and CV hand motion analysis. Timing and instrument-use metrics were obtained through video reviews. IPS, idle and active times, elapsed time to division of pectoralis minor, type and number of instruments used, and calculated Shannon Joint Entropy values discriminated among the three groups of participants. Experts had lowest entropy values, idle and active times, and shortest time to divide pectoralis minor, using fewer instruments. Residents improved with training, not reaching expert levels, but showed deterioration 12-18 months later. Anatomists' results differed substantially from expert and resident surgeons. Surgeon's IPS scores mirrored the results of hand motion analysis. Conclusions Hand motion analysis techniques, which were congruent with IPS evaluations, can discriminate levels of surgical skill and training.
UR - http://www.scopus.com/inward/record.url?scp=85021813654&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85021813654
SN - 1071-1813
VL - 0
SP - 691
EP - 695
JO - Proceedings of the Human Factors and Ergonomics Society
JF - Proceedings of the Human Factors and Ergonomics Society
Y2 - 19 September 2016 through 23 September 2016
ER -