ArticleSensors (Basel, Switzerland)2020
LAPKaans: Tool-Motion Tracking and Gripping Force-Sensing Modular Smart Laparoscopic Training System.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Role of haptic feedback technologies and novel engineering developments for surgical training and robot-assisted surgery.Frontiers in robotics and AI · 2025Review
- Surgical skill analysis focused on tissue traction in laparoscopic wet lab training.Surgery open science · 2024Article
- An intelligent grasper to provide real-time force feedback to shorten the learning curve in laparoscopic training.BMC medical education · 2024Article
- Clinical applications of robotic surgery platforms: a comprehensive review.Journal of robotic surgery · 2024Review
- Effectiveness of a vision-based handle trajectory monitoring system in studying robotic suture operation.Journal of robotic surgery · 2023Article
- Comparative evaluation of three commercially available markerless depth sensors for close-range use in surgical simulation.International journal of computer assisted radiology and surgery · 2023Article
- VR, reconstructive urology and the future of surgery education.Nature reviews. Urology · 2023Article
- Towards next generation digital twin in robotics: Trends, scopes, challenges, and future.Heliyon · 2023Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Laparoscopic surgery demands highly skilled surgeons. Traditionally, a surgeon's knowledge is acquired by operating under a mentor-trainee method. In recent years, laparoscopic simulators have gained ground as tools in skill acquisition. Despite the wide range of laparoscopic simulators available, few provide objective feedback to the trainee. Those systems with quantitative feedback tend to be high-end solutions with limited availability due to cost. A modular smart trainer was developed, combining tool-tracking and force-using employing commercially available sensors. Additionally, a force training system based on polydimethylsiloxane (PDMS) phantoms for sample stiffness differentiation is presented. This prototype was tested with 39 subjects, between novices (13), intermediates (13), and experts (13), evaluating execution differences among groups in training exercises. The estimated cost is USD $200 (components only), not including laparoscopic instruments. The motion system was tested for noise reduction and position validation with a mean error of 0.94 mm. Grasping force approximation showed a correlation of 0.9975. Furthermore, differences in phantoms stiffness effectively reflected user manipulation. Subject groups showed significant differences in execution time, accumulated distance, and mean and maximum applied grasping force. Accurate information was obtained regarding motion and force. The developed force-sensing tool can easily be transferred to a clinical setting. Further work will consist on a validation of the simulator on a wider range of tasks and a larger sample of volunteers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.