Background: It is a tacit assumption that clinically based expertise in laparoscopic tissue manipulation entails skilfulness in angled laparoscope navigation. The main objective of this study was to investigate the relation between these skills. To this end, face and construct validity had to be established for the place arrow (PA) and camera navigation (CN) tasks on the SimSurgery SEP.
Methods: Thirty-three novices (no laparoscopy experience) and 33 experienced participants (>50 laparoscopic procedures and familiar with angled laparoscopy) performed both tasks twice, on one of two hardware platforms (SimSurgery SimPack or Xitact/Mentice IHP), and rated the realism and didactic value of SimSurgery SEP on five-point scales.
Results: Both tasks were rated by the experienced participants as realistic (CN: 3.7; PA: 4.1) and SimSurgery SEP as a user-friendly environment to train basic skills (4.1). Both tasks were performed in less time by the experienced group, with shorter tip trajectories. For both groups jointly, the time to accomplish each task correlated with the tip trajectory and also with the time and tip trajectories of the opposite task (Spearman's correlation, p
Conclusions: A correlation was not always found between the performances on the two tasks, which suggests that clinically based expertise in tissue manipulation does not automatically entail skilfulness in angled laparoscope navigation, and vice versa. Training and assessment of basic laparoscopic skills should focus on these tasks independently. More research is needed to better identify the skills and required proficiency levels for different laparoscopic tasks.
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Sensors (Basel)
December 2024
SOTI Aerospace, SOTI Inc., Mississauga, ON L5N 8L9, Canada.
Indoor navigation is becoming increasingly essential for multiple applications. It is complex and challenging due to dynamic scenes, limited space, and, more importantly, the unavailability of global navigation satellite system (GNSS) signals. Recently, new sensors have emerged, namely event cameras, which show great potential for indoor navigation due to their high dynamic range and low latency.
View Article and Find Full Text PDFComput Med Imaging Graph
December 2024
School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, Beijing, PR China; Zhengzhou Research Institute, Beijing Institute of Technology, Zhengzhou, 450000, Henan, PR China. Electronic address:
In skull base surgery, the method of using a probe to draw or 3D scanners to acquire intraoperative facial point clouds for spatial registration presents several issues. Manual manipulation results in inefficiency and poor consistency. Traditional registration algorithms based on point clouds are highly dependent on the initial pose.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada.
Autonomous technologies have revolutionized transportation, military operations, and space exploration, necessitating precise localization in environments where traditional GPS-based systems are unreliable or unavailable. While widespread for outdoor localization, GPS systems face limitations in obstructed environments such as dense urban areas, forests, and indoor spaces. Moreover, GPS reliance introduces vulnerabilities to signal disruptions, which can lead to significant operational failures.
View Article and Find Full Text PDFSci Rep
December 2024
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
Autonomous vehicles, often known as self-driving cars, have emerged as a disruptive technology with the promise of safer, more efficient, and convenient transportation. The existing works provide achievable results but lack effective solutions, as accumulation on roads can obscure lane markings and traffic signs, making it difficult for the self-driving car to navigate safely. Heavy rain, snow, fog, or dust storms can severely limit the car's sensors' ability to detect obstacles, pedestrians, and other vehicles, which pose potential safety risks.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
School of Artificial Intelligence, Tongmyong University, Busan 48520, Republic of Korea.
Depth estimation plays a pivotal role in advancing human-robot interactions, especially in indoor environments where accurate 3D scene reconstruction is essential for tasks like navigation and object handling. Monocular depth estimation, which relies on a single RGB camera, offers a more affordable solution compared to traditional methods that use stereo cameras or LiDAR. However, despite recent progress, many monocular approaches struggle with accurately defining depth boundaries, leading to less precise reconstructions.
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