Task analysis of laparoscopic camera control schemes

Ellis, R. Darin; Munaco, Anthony J.; Reisner, Luke A.; Klein, Michael D.; Composto, Anthony; Pandya, Abhilash; King, Brady W.

doi:10.1002/rcs.1716

Cited by 16 publications

(18 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed surgical data set and tools created herein could be leveraged to potentially enhance training for surgeons. This work complements our work in task analysis based on surgical datasets [18,20]. In addition, these recordings could be ubiquitously shared beyond the local hospitals and be preserved for distribution to future generations of surgeons.…”

Section: Discussionmentioning

confidence: 73%

“…Movement data for a limited set of bench-top tests are available [17] for research use, but the data is limited to a few examples and is not sufficiently large for deep learning. Any serious attempt at deep machine learning for complex surgical tasks requires a large amount of registered, time-synchronized, and high quality surgical data, as pointed out by Satava and others [18][19][20][21].…”

Section: Data For Automation Of Surgical Procedures Using Machine Leamentioning

confidence: 99%

See 1 more Smart Citation

A Robotic Recording and Playback Platform for Training Surgeons and Learning Autonomous Behaviors Using the da Vinci Surgical System

et al. 2019

Self Cite

View full text Add to dashboard Cite

This paper describes a recording and playback system developed using a da Vinci Standard Surgical System and research kit. The system records stereo laparoscopic videos, robot arm joint angles, and surgeon–console interactions in a synchronized manner. A user can then, on-demand and at adjustable speeds, watch stereo videos and feel recorded movements on the hand controllers of entire procedures or sub procedures. Currently, there is no reported comprehensive ability to capture expert surgeon movements and insights and reproduce them on hardware directly. This system has important applications in several areas: (1) training of surgeons, (2) collection of learning data for the development of advanced control algorithms and intelligent autonomous behaviors, and (3) use as a “black box” for retrospective error analysis. We show a prototype of such an immersive system on a clinically-relevant platform along with its recording and playback fidelity. Lastly, we convey possible research avenues to create better systems for training and assisting robotic surgeons.

show abstract

Section: Discussionmentioning

confidence: 73%

Section: Data For Automation Of Surgical Procedures Using Machine Leamentioning

confidence: 99%

A Robotic Recording and Playback Platform for Training Surgeons and Learning Autonomous Behaviors Using the da Vinci Surgical System

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, when the surgeon starts suturing, the algorithm can recognize it in the first 8 s with 96% accuracy. Then, the camera can automatically switch to the predefined mode for this task, which has been defined based on the best possible schema such as position of the camera or zooming level .…”

Section: Discussionmentioning

confidence: 86%

“…The ultimate goal of RMIS is to program the surgical robot to perform certain difficult or complex surgery in an autonomous manner. However, there is no technical roadmap to a fully autonomous surgical system at the present time . Current RMIS systems operate in a master–slave mode, relying exclusively on direct surgeon input .…”

Section: Introductionmentioning

confidence: 99%

“…For example, camera control in current RMIS platforms is an additional task under direct control of the surgeon. In the current FDA‐approved system, the da Vinci surgical platform (Intuitive Surgical, Sunnyvale, CA, USA) , many interface parameters are set once and remain at the same level throughout the operation while different surgical tasks and motions may require different camera behaviors . For instance, it has been shown that a wide view is desirable for the looping phase while the view should be narrow when grabbing the free end of the suture in a knot tying task.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distance‐based time series classification approach for task recognition with application in surgical robot autonomy

Fard

Pandya

Chinnam

et al. 2016

Robotics Computer Surgery

Self Cite

View full text Add to dashboard Cite

show abstract

A learning robot for cognitive camera control in minimally invasive surgery

et al. 2021

View full text Add to dashboard Cite

Background We demonstrate the first self-learning, context-sensitive, autonomous camera-guiding robot applicable to minimally invasive surgery. The majority of surgical robots nowadays are telemanipulators without autonomous capabilities. Autonomous systems have been developed for laparoscopic camera guidance, however following simple rules and not adapting their behavior to specific tasks, procedures, or surgeons. Methods The herein presented methodology allows different robot kinematics to perceive their environment, interpret it according to a knowledge base and perform context-aware actions. For training, twenty operations were conducted with human camera guidance by a single surgeon. Subsequently, we experimentally evaluated the cognitive robotic camera control. A VIKY EP system and a KUKA LWR 4 robot were trained on data from manual camera guidance after completion of the surgeon’s learning curve. Second, only data from VIKY EP were used to train the LWR and finally data from training with the LWR were used to re-train the LWR. Results The duration of each operation decreased with the robot’s increasing experience from 1704 s ± 244 s to 1406 s ± 112 s, and 1197 s. Camera guidance quality (good/neutral/poor) improved from 38.6/53.4/7.9 to 49.4/46.3/4.1% and 56.2/41.0/2.8%. Conclusions The cognitive camera robot improved its performance with experience, laying the foundation for a new generation of cognitive surgical robots that adapt to a surgeon’s needs.

show abstract

Task analysis of laparoscopic camera control schemes

Abstract: The results can be used to develop better robotic control algorithms that will be more responsive to surgeons' needs. Copyright © 2015 John Wiley & Sons, Ltd.

Cited by 16 publications

References 22 publications

A Robotic Recording and Playback Platform for Training Surgeons and Learning Autonomous Behaviors Using the da Vinci Surgical System

A Robotic Recording and Playback Platform for Training Surgeons and Learning Autonomous Behaviors Using the da Vinci Surgical System

Distance‐based time series classification approach for task recognition with application in surgical robot autonomy

A learning robot for cognitive camera control in minimally invasive surgery

Contact Info

Product

Resources

About