Efficacy of novel robotic camera vs a standard laparoscopic camera.

Surg Innov

Department of Surgery, Gastric and Mixed Tumor, Memorial Sloan Kettering Cancer, New York, NY 10032, USA.

Published: December 2005

To improve visualization during minimal access surgery, a novel robotic camera has been developed. The prototype camera is totally insertable, has 5 degrees of freedom, and is remotely controlled. This study compared the performance of laparoscopic surgeons using both a laparoscope and the robotic camera. The MISTELS (McGill Inanimate System for the Training and Evaluation of Laparoscopic Skill) tasks were used to test six laparoscopic fellows and attending surgeons. Half the surgeons used the laparoscope first and half used the robotic camera first. Total scores from the MISTELS sessions in which the laparoscope was used were compared with the sessions in which the robotic camera was used and then analyzed with a paired t test (P < .05 was considered significant). All six surgeons tested showed no significant difference in their MISTELS task performance on the robotic camera compared with the standard laparoscopic camera. The mean MISTELS score of 963 for all subjects who used a laparoscope and camera was not significantly different than the mean score of 904 for the robotic camera (P = .17). This new robotic camera prototype allows for equivalent performance on a validated laparoscopic assessment tool when compared with performance using a standard laparoscope.

Download full-text PDF

Source
http://dx.doi.org/10.1177/155335060501200405DOI Listing

Publication Analysis

Top Keywords

robotic camera
32
camera
12
robotic
8
novel robotic
8
standard laparoscopic
8
laparoscopic camera
8
compared performance
8
surgeons laparoscope
8
camera mistels
8
laparoscopic
6

Similar Publications

The emergence of augmented reality (AR) in surgical procedures could significantly enhance accuracy and outcomes, particularly in the complex field of orthognathic surgery. This study compares the effectiveness and accuracy of traditional drilling guides with two AR-based navigation techniques: one utilizing ArUco markers and the other employing small-workspace infrared tracking cameras for a drilling task. Additionally, an alternative AR visualization paradigm for surgical navigation is proposed that eliminates the potential inaccuracies of image detection using headset cameras.

View Article and Find Full Text PDF

Purpose: Assessing surgical skills is vital for training surgeons, but creating objective, automated evaluation systems is challenging, especially in robotic surgery. Surgical procedures generally involve dissection and exposure (D/E), and their duration and proportion can be used for skill assessment. This study aimed to develop an AI model to acquire D/E parameters in robot-assisted radical prostatectomy (RARP) and verify if these parameters could distinguish between novice and expert surgeons.

View Article and Find Full Text PDF

In recent years, robotic assistance has become increasingly used and applied in minimally invasive surgeries. A new cooperative surgical robot system that includes a joystick-guided robotic scope holder was developed in this study, and its feasibility for use in minimally invasive abdominal surgery was evaluated in a preclinical setting. The cooperative surgical robot consists of a six-degree-of-freedom collaborative robot arm and a one-degree-of-freedom bidirectional telescopic end-effector specializing in surgical assistance.

View Article and Find Full Text PDF

Introduction: The rapid urbanization of rural regions, along with an aging population, has resulted in a substantial manpower scarcity for agricultural output, necessitating the urgent development of highly intelligent and accurate agricultural equipment technologies.

Methods: This research introduces YOLOv8-PSS, an enhanced lightweight obstacle detection model, to increase the effectiveness and safety of unmanned agricultural robots in intricate field situations. This YOLOv8-based model incorporates a depth camera to precisely identify and locate impediments in the way of autonomous agricultural equipment.

View Article and Find Full Text PDF

G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection.

Sensors (Basel)

December 2024

School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130022, China.

In industrial applications, robotic arm grasp detection tasks frequently suffer from inadequate accuracy and success rates, which result in reduced operational efficiency. Although existing methods have achieved some success, limitations remain in terms of detection accuracy, real-time performance, and generalization ability. To address these challenges, this paper proposes an enhanced grasp detection model, G-RCenterNet, based on the CenterNet framework.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!