1. Using Video Motion Analysis to Quantify Technical Performance
Carly E. Glarner, MD,* Yue-Yung Hu, MD,* Chia-Hsiung Chen, MS,
Robert G. Radwin, PhD, Qianqian Zhao, MS, Mark Craven, PhD, Carla Pugh, MD, PhD, Matthew Carty, MD, Caprice C. Greenberg MD, MPH, FACS
(*Co-first authors)

2. Disclosures
No relevant conflict of interests

3. Motion Analysis Tracks detailed metrics Technological Advances
Objective and reproducible
More specific and precise feedback
Relies on sensors on surgeon’s hand or instrument
Technological Advances
Increased availability of recording devices
Marker-less video based motion analysis
Developed within Industrial Engineering

4. Aim
To determine if motion analysis using marker-less video-based review could be adapted for the analysis of technical skill performance in the OR

5. Methods: Case and Patient Selection
Index Case:
Reduction mammoplasty
Attending and resident operate simultaneously
Benign breast tissue symmetrical
Patients:
Women undergoing bilateral reduction mammoplasty
Both surgeon and patient consent obtained

6. Methods: Data Collection
44 Potential cases between 2/29/12-6/22/12
Permission obtained from 6 surgeons
19 Patients consented
11 Cases recorded
9 Cases had in-light camera view
6 Cases yielded usable video for analysis

7. Methods: Coding Multimedia Video Task Analysis (MVTA)
Representative surgical tasks
Cutting with electro-cautery (bovie)
Cutting with scalpel
Suturing
Instrument tying

8. MVTA

9. Methods: Motion Analysis
Spatio-temporal characteristics of the hand movements were extracted
Analyzed using an automated, video-based program
Marker-less
Similar results to traditional sensor-based motion analyses performed in the laboratory setting

10. Hand Motion Analysis Software

11. Methods: Statistical Analysis
Analysis of displacement, velocity, and acceleration by:
Task
Surgeon level
Descriptive statistics were generated for:
Dominant hand
Non-dominant hand
Difference between hands

12. Results: Cutting with Bovie

13. Results: Cutting with Scalpel

14. Results: Suturing

15. Results: Instrument Tying
p=0.05
p=0.01

16. Conclusions
Video- based motion analysis is a feasible way to collect data on technical performance
No markers or other types of sensors
Applicable for open operations
Future directions
Analyze a larger range of surgical abilities and operation types
Continue to develop metrics
Better characterize acquisition of technical skills
Making the analysis process more automated

17. Thank you Participants Research Team Funding
BWH Plastic Surgeons and Residents
BWH Patients
Research Team
Yue-Yung Hu
Chia-Hsiung Chen
Robert Radwin
Qianqian Zhao
Mark Craven
Carla Pugh
Matthew Carty
Caprice Greenberg
Funding
T32 Surgical Oncology Grant
David M. Mahvi Research Fellowship Award
SUS-KSEA Resident Scholarship