Objective Evaluation of Laparoscopic Experience Based on Muscle Electromyography and Accelerometry Performing Circular Pattern Cutting Tasks: A Pilot Study.

Purpose.The aim of this work is to present a new physical laparoscopy simulator with an electromyography (EMG)/accelerometry-based muscle activity recording system, EvalLap EMG-ACC, and perform objective evaluation of laparoscopic skills based on the quantification of muscle activity of participants with different levels of laparoscopic experience. Methods. EMG and ACC signals were obtained from 14 participants (6 experts, 8 medical students) performing circular pattern cutting tasks using a laparoscopic box trainer with the Trigno (Delsys Inc, Natick, MA) portable wireless system of 16 wireless sensors. Sensors were placed on the proximal and distal muscles of the upper extremities. Seven evaluation metrics were proposed and compared between skilled and novice surgeons. Results. The proximal and distal arm muscles (trapezius, deltoids, biceps, and forearms) were most active while executing laparoscopic tasks. Laparoscopic experience was associated with differences in EMG amplitude (Aavg), muscle activity (iEMG), hand acceleration (iACH), user movement (iAC), and muscle fatigue. For the cutting task, the deltoid, bicep, forearm EMG amplitude, and user movement significantly differed between experience groups. Conclusion. This pilot study demonstrates that different muscle groups are preferentially activated during laparoscopic tasks depending on the level of surgical experience. Expert surgeons showed less muscle activity compared with novices. EvalLap EMG-ACC represents a promising means to distinguish surgeons with basic cutting skills from those who have not yet developed these skills.

Integration of Comprehensive Metrics into the PsT1 Neuroendoscopic Training System.

OBJECTIVE: Metric-based surgical training can be used to quantify the level and progression of neurosurgical performance to optimize and monitor training progress. Here we applied innovative metrics to a physical neurosurgery trainer to explore whether these metrics differentiate between different levels of experience across different tasks. METHODS: Twenty-four participants (9 experts, 15 novices) performed 4 tasks (dissection, spatial adaptation, depth adaptation, and the A-B-A task) using the PsT1 training system. Four performance metrics (collision, precision, dissected area, and time) and 6 kinematic metrics (dispersion, path length, depth perception, velocity, acceleration, and motion smoothness) were collected. RESULTS: For all tasks, the execution time (t) of the experts was significantly lower than that of novices (P < 0.05). The experts performed significantly better in all but 2 of the other metrics, dispersion and sectional area, corresponding to the A-B-A task and dissection task, respectively, for which they showed a nonsignificant trend towards better performance (P = 0.052 and P = 0.076, respectively). CONCLUSIONS: It is possible to differentiate between the skill levels of novices and experts according to parameters derived from the PsT1 platform, paving the way for the quantitative assessment of training progress using this system. During the current coronavirus disease 2019 pandemic, neurosurgical simulators that gather surgical performance metrics offer a solution to the educational needs of residents.

Image processing for AFB segmentation in bacilloscopies of pulmonary tuberculosis diagnosis.

Image segmentation applied to medical image analysis is still a critical and important task. Although there exist several segmentation algorithms that have been widely studied in literature, these are subject to segmentation problems such as over- and under-segmentation as well as non-closed edges. In this paper, a simple method that combines well-known segmentation algorithms is presented. This method is applied to detect acid-fast bacilli (AFB) in bacilloscopies used to diagnose pulmonary tuberculosis (TB). This diagnosis can be performed through different tests, and the most used worldwide is smear microscopy because of its low cost and effectiveness. This diagnosis technique is based on the analysis and counting of the bacilli in the bacilloscopy observed under an optical microscope. The proposed method is used to segment the bacilli in digital images from bacilloscopies processed using Ziehl-Neelsen (ZN) staining. The proposed method is fast, has a low computational cost and good efficiency compared to other methods. The bacilli image segmentation is performed by image processing and analysis techniques, probability concepts and classifiers. In this work, a Bayesian classifier based on a Gaussian mixture model (GMM) is used. The segmentations' results are validated by using the Jaccard index, which indicates the efficiency of the classifier.

Optimizing the positional relationships between instruments used in laparoscopic simulation using a simple trigonometric method.

BACKGROUND: Various methods for evaluating laparoscopic skill have been reported, but without detailed information on the configuration used they are difficult to reproduce. Here we present a method based on the trigonometric relationships between the instruments used in a laparoscopic training platform in order to provide a tool to aid in the reproducible assessment of surgical laparoscopic technique. MATERIALS AND METHODS: The positions of the instruments were represented using triangles. Basic trigonometry was used to objectively establish the distances among the working ports RL, the placement of the optical port h', and the placement of the surgical target OT. RESULTS: The optimal configuration of a training platform depends on the selected working angles, the intracorporeal/extracorporeal lengths of the instrument, and the depth of the surgical target. We demonstrate that some distances, angles, and positions of the instruments are inappropriate for satisfactory laparoscopy. CONCLUSIONS: By applying basic trigonometric principles we can determine the ideal placement of the working ports and the optics in a simple, precise, and objective way. In addition, because the method is based on parameters known to be important in both the performance and quantitative quality of laparoscopy, the results are generalizable to different training platforms and types of laparoscopic surgery.

Is the digitization of laparoscopic movement using accessible alternative technologies possible?

It is widely documented that laparoscopic surgeons require training, and an objective evaluation of the training that they receive. The most advanced evaluation systems integrate the digitization of the movement of laparoscopic tools. A great number of these systems, however, do not permit the use of real tools and their high cost limits their academic impact. Likewise, it is documented that new and accessible systems need to be developed. The aim of this article is to explore the possibility of digitizing the movement of laparoscopic tools in a three-dimensional workspace, using accessible alternative technology. Our proposal uses a commercial Wii video game control in conjunction with a program for determining kinematic variables during the execution of a recognition task.