Visual Feedback for Skill Acquisition in Cataract Surgery

Last updated: 05/02/2017 12.05pm


The project aims at developing a system which helps train novice surgeons with the aid of visual feedback.

  • Students: Abhilash Balachandran
  • Mentor(s): Swaroop Vedulla, Austin Reiter

Background, Specific Aims, and Significance

Currently, feedback to support technical skill acquisition among trainees in ophthalmology is through qualitative verbal instruction and demonstration. Directed feedback can facilitate deliberate practice and effective skill acquisition. This project aims to develop visual feedback to support technical skill training in cataract surgery during task performance. The aim of this project is to develop a system:

  • which records tool motion video and tool forces
  • estimates a relationship between tool motion and tool force
  • Visually overlays the tool forces
  • Compares tool force patterns between novices and experts

This is important since it would help in assessing the expertise and also provide a means for novice surgeons to asses their experience.


* Minimum: (04/15/2016)

  1. Setup to record tool force video and forces
  2. Visual overlay of tool forces to aid surgeons
  • Expected: (05/10/2016)
    1. Collect data of tool motion and forces from experts and novices
  • Maximum: (05/18/2016)
    1. Estimate tool force pattern at any point of the procedure
    2. Compare tool force pattern between experts and novices

Technical Approach

The project involves recording tool motion video and force during capsulorhexis. In order to do this, a phantom was constructed using cardboard and wax paper (this was decided after trying a lot of other models). The capsulorrexis procedure is then performed on this phantom using the da vinci research kit(dark). The corresponding tool motion video and force data are recorded. Data is recorded for a number of novices and experts. Using the collected data, forces are estimated at any position during the procedure using machine learning regression techniques. The forces are then visually overlayed to aid any surgeon performing the task next. Also, from the tool force pattern, the expertise of the surgeon is judged.


Access to da vinci research kit = Completed (02/15/2017)

Phantom to simulate the task = Completed (04/20/2017)

Force sensor setup with dos bridge = Completed (03/15/2017)

Setup to record data (Calibration, etc.) = Completed (04/01/2017)

Data collection - Experts and novices = Acquired but not yet completed

Milestones and Status

  1. Milestone name: Phantom to simulate task
    • Planned Date: 02/30
    • Expected Date: 02/30
    • Status: Completed on 04/20. Delay due to complications with force sensor and reliability for repeatability
  2. Milestone name: Setup for data collection
    • Planned Date: 03/30
    • Expected Date: 03/30
    • Status: Completed
  3. Milestone name: Data Collection
    • Planned Date: 04/15
    • Expected Date: 05/10
    • Status: Incomplete
  4. Milestone name: Force estimation
    • Planned Date: 05/10
    • Expected Date: 05/18
    • Status: Incomplete

Reports and presentations

Project Bibliography

  • [1] Cremers SL, Lora AN, Ferrufino-Ponce ZK. Global rating assessment of skills in intraocular surgery (GRASIS). Ophthalmology. 2005;112(10):1655-1660.
  • [2] Saleh GM, Gauba V, Mitra A, Litwin AS, Chung AK, Benjamin L. Objective structured assessment of cataract surgical skill. Arch Ophthalmol. 2007;125(3):363-366.
  • [3] Fisher JB, Binenbaum G, Tapino P, Volpe NJ. Development and face and content validity of an eye surgical skills assessment test for ophthalmology residents. Ophthalmology. 2006;113(12):2364-2370.
  • [4] Martin JA, Regehr G, Reznick R, et al. Objective structured assessment of technical skill (OSATS) for surgical residents. Br J Surg. 1997;84(2):273-278.
  • [5] Cremers SL, Ciolino JB, Ferrufino-Ponce ZK, Henderson BA. Objective assessment of skills in intraocular surgery (OASIS). Ophthalmology. 2005;112(7):1236-1241.
  • [6] Gauba V, Saleh GM, Goel S. Ophthalmic plastic surgical skills assessment tool. Ophthal Plast Reconstr Surg. 2008;24(1):43-46.
  • [7] Bay H, Ess A, Tuytelaars T, Van Gool L. Speeded-Up Robust Features (SURF).Comput Vis Image Understanding. 2008;110(3):346-359. doi:10.1016/j.cviu.2007.09.014. 
  • [8] Carlo T, Kanade T. Detection and Tracking of Point Features. Pittsburgh, PA: Carnegie Mellon University; 1991. Technical Report CMU-CS-91-132.

Other Resources and Project Files

courses/446/2017/446-2017-22/project.txt · Last modified: 2017/05/18 18:41 by