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Comparison of Performance Metrics for Real-Time Haptic Feedback in Surgical Skill Training

EasyChair Preprint no. 8179

2 pagesDate: June 1, 2022


Endovascular surgery requires significant manual dexterity, which is usually gained through training and specialized practice. Existing training methods provide feedback only after the completion of a surgical task and do not provide the trainee with insight into task performance strategies that may help improve performance. To address this gap, we examine three metrics that measure movement smoothness from endovascular tooltip motion that are known to correlate with expertise, namely Spectral Arc Length (SPARC), Average Velocity, and Idle Time. Using a post hoc analysis, we explored the distribution of feedback (good, fair, or poor performance) that participants would have received when performing endovascular navigation tasks. The ranges of scores for each metric were determined from data collected in prior studies. Spectral Arc Length was determined to be best suited for real-time performance feedback when compared to Average Velocity and Idle Time, since scores based on this metric were more distributed across the three performance levels and more frequently generated feedback indicating good performance by the trainee.

Keyphrases: endovascular surgery, Haptics, performance feedback, training, Virtual Reality

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lianne R. Johnson and Michael D. Byrne and Marcia K. O'Malley},
  title = {Comparison of Performance Metrics for Real-Time Haptic Feedback in Surgical Skill Training},
  howpublished = {EasyChair Preprint no. 8179},

  year = {EasyChair, 2022}}
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