JIGSAWS

JHU-ISI Gesture and Skill Assessment Working Set

Dataset Information
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Overview

The JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS) is a surgical activity dataset for human motion modeling. The data was collected through a collaboration between The Johns Hopkins University (JHU) and Intuitive Surgical, Inc. (Sunnyvale, CA. ISI) within an IRB-approved study. The release of this dataset has been approved by the Johns Hopkins University IRB. The dataset was captured using the da Vinci Surgical System from eight surgeons with different levels of skill performing five repetitions of three elementary surgical tasks on a bench-top model: suturing, knot-tying and needle-passing, which are standard components of most surgical skills training curricula. The JIGSAWS dataset consists of three components:

  • kinematic data: Cartesian positions, orientations, velocities, angular velocities and gripper angle describing the motion of the manipulators.
  • video data: stereo video captured from the endoscopic camera. Sample videos of the JIGSAWS tasks can be downloaded from the official webpage.
  • manual annotations including:
  • gesture (atomic surgical activity segment labels).
  • skill (global rating score using modified objective structured assessments of technical skills).
  • experimental setup: a standardized cross-validation experimental setup that can be used to evaluate automatic surgical gesture recognition and skill assessment methods.

Source: https://cirl.lcsr.jhu.edu/research/hmm/datasets/jigsaws_release
Image Source: https://cirl.lcsr.jhu.edu/research/hmm/datasets/jigsaws_release

Variants: JIGSAWS

Associated Benchmarks

This dataset is used in 3 benchmarks:

Recent Benchmark Submissions

Task Model Paper Date
Action Quality Assessment RICA^2 RICA2: Rubric-Informed, Calibrated Assessment of … 2024-08-04
Action Quality Assessment RICA^2 (Deterministic) RICA2: Rubric-Informed, Calibrated Assessment of … 2024-08-04
Action Quality Assessment DAE-MT Auto-Encoding Score Distribution Regression for … 2021-11-22
Action Quality Assessment DAE-MLP Auto-Encoding Score Distribution Regression for … 2021-11-22
Action Quality Assessment DAE-CoRe Auto-Encoding Score Distribution Regression for … 2021-11-22
Action Segmentation MRG-Net Relational Graph Learning on Visual … 2020-11-03
Action Segmentation RL+Tree Automatic Gesture Recognition in Robot-assisted … 2020-02-20
Action Segmentation RL (full) Deep Reinforcement Learning for Surgical … 2018-06-21
Surgical Skills Evaluation CNN Evaluating surgical skills from kinematic … 2018-06-07
Action Segmentation SDL+SC-CRF End-to-End Fine-Grained Action Segmentation and … 2018-01-29
Action Segmentation TricorNet TricorNet: A Hybrid Temporal Convolutional … 2017-05-22
Action Segmentation TCN Temporal Convolutional Networks: A Unified … 2016-08-29
Surgical Skills Evaluation Bidir. LSTM Recognizing Surgical Activities with Recurrent … 2016-06-20
Action Segmentation ST-CNN+Seg Segmental Spatiotemporal CNNs for Fine-grained … 2016-02-09

Research Papers

Recent papers with results on this dataset:

External Links: