Crisis management in the operating room: A systematic review of simulation training to develop non-technical skills.

Aims: Crises in the operating room, often resulting from human factors, endangers patient safety. Simulation-based training to develop non-technical skills shows promise in managing these crises. This review examines the simulation techniques, targeted healthcare professionals, non-technical skills, crisis scenarios, and evaluation metrics used in operating room crisis management training.

Virtual reality-based simulation improves rotator cuff repair skill: A randomized transfer validity study.

Background: Although virtual reality (VR) simulators have demonstrated their efficiency for basic technical skill training of healthcare professionals, validation for more complex and sequential procedures, especially in arthroscopic surgery, is still warranted. We hypothesized that the VR-based training simulation improves arthroscopic cuff repair skills when transferred to realistic visual and haptic conditions.

Hypothesis: VR-based training simulation improves arthroscopic cuff repair skills when transferred to realistic visual and haptic conditions.

Comparison of the OpenPose system and the reference optoelectronic system for gait analysis of lower-limb angular parameters in children.

Introduction: Quantitative Gait Analysis (QGA) is the gold-standard for detailed study of lower-limb movement, angles and forces, especially in pediatrics, providing a decision aid for treatment and for assessment of results. However, widespread use of QGA is hindered by the need for specific equipment and trained personnel and high costs. Recently, the OpenPose system used algorithms for 2D video movement analysis, to determine joint points and angles without any supplementary equipment or great expertise.

Automated assessment of non-technical skills by heart-rate data.

Purpose: Observer-based scoring systems, or automatic methods, based on features or kinematic data analysis, are used to perform surgical skill assessments. These methods have several limitations, observer-based ones are subjective, and the automatic ones mainly focus on technical skills or use data strongly related to technical skills to assess non-technical skills. In this study, we are exploring the use of heart-rate data, a non-technical-related data, to predict values of an observer-based scoring system thanks to random forest regressors.

The influence of virtual reality simulation on surgical residents' heart rate during an assessment of arthroscopic technical skills: A prospective, paired observational study.

Hypothesis: To demonstrate that a virtual reality (VR) simulation training program reduces heart rate variability during an assessment of surgical trainees' technical skills in arthroscopy.

Study Design: Prospective observational matched study.

Materials & Methods: Thirty-six orthopaedic surgery residents, new to arthroscopy, received standard training in arthroscopic knee surgery, supplemented by additional monthly training for 6months on a VR simulator for 16 of them.

Virtual reality simulation training improve diagnostic knee arthroscopy and meniscectomy skills: a prospective transfer validity study.

Purpose: Limited data exist on the actual transfer of skills learned using a virtual reality (VR) simulator for arthroscopy training because studies mainly focused on VR performance improvement and not on transfer to real word (transfer validity). The purpose of this single-blinded, controlled trial was to objectively investigate transfer validity in the context of initial knee arthroscopy training.

Methods: For this study, 36 junior resident orthopaedic surgeons (postgraduate year one and year two) without prior experience in arthroscopic surgery were enrolled to receive standard knee arthroscopy surgery training (NON-VR group) or standard training plus training on a hybrid virtual reality knee arthroscopy simulator (1 h/month) (VR group).

sEMG-based Motion Recognition for Robotic Surgery Training - A Preliminary Study.

Robotic surgery represents a major breakthrough in the evolution of medical technology. Accordingly, efficient skill training and assessment methods should be developed to meet the surgeon's need of acquiring such robotic skills over a relatively short learning curve in a safe manner. Different from conventional training and assessment methods, we aim to explore the surface electromyography (sEMG) signal during the training process in order to obtain semantic and interpretable information to help the trainee better understand and improve his/her training performance.

Physical environment of the operating room during cesarean section: A systematic review.

Introduction: Environmental factors in the operating room during cesarean sections are likely important for both women/birthing people and their babies but there is currently a lack of rigorous literature about their evaluation. The principal aim of this study was to systematically examine studies published on the physical environment in the obstetrical operating room during c-sections and its impact on mother and neonate outcomes. The secondary objective was to identify the sensors used to investigate the operating room environment during cesarean sections.

Gaze behavior is related to objective technical skills assessment during virtual reality simulator-based surgical training: a proof of concept.

Purpose: Simulation-based training allows surgical skills to be learned safely. Most virtual reality-based surgical simulators address technical skills without considering non-technical skills, such as gaze use. In this study, we investigated surgeons' visual behavior during virtual reality-based surgical training where visual guidance is provided.

A systematic review of annotation for surgical process model analysis in minimally invasive surgery based on video.

Background: Annotated data are foundational to applications of supervised machine learning. However, there seems to be a lack of common language used in the field of surgical data science. The aim of this study is to review the process of annotation and semantics used in the creation of SPM for minimally invasive surgery videos.

PEg TRAnsfer Workflow recognition challenge report: Do multimodal data improve recognition?

Background And Objective: In order to be context-aware, computer-assisted surgical systems require accurate, real-time automatic surgical workflow recognition. In the past several years, surgical video has been the most commonly-used modality for surgical workflow recognition. But with the democratization of robot-assisted surgery, new modalities, such as kinematics, are now accessible.

"Stand-up straight!": human pose estimation to evaluate postural skills during orthopedic surgery simulations.

Purpose: Surgery simulators can be used to learn technical and non-technical skills and, to analyse posture. Ergonomic skill can be automatically detected with a Human Pose Estimation algorithm to help improve the surgeon's work quality. The objective of this study was to analyse the postural behaviour of surgeons and identify expertise-dependent movements.

Review of automated performance metrics to assess surgical technical skills in robot-assisted laparoscopy.

Introduction: Robot-assisted laparoscopy is a safe surgical approach with several studies suggesting correlations between complication rates and the surgeon's technical skills. Surgical skills are usually assessed by questionnaires completed by an expert observer. With the advent of surgical robots, automated surgical performance metrics (APMs)-objective measures related to instrument movements-can be computed.

MIcro-surgical anastomose workflow recognition challenge report.

Background And Objective: Automatic surgical workflow recognition is an essential step in developing context-aware computer-assisted surgical systems. Video recordings of surgeries are becoming widely accessible, as the operational field view is captured during laparoscopic surgeries. Head and ceiling mounted cameras are also increasingly being used to record videos in open surgeries.

Validation of virtual reality arthroscopy simulator relevance in characterising experienced surgeons.

Background: Virtual reality (VR) simulation is particularly suitable for learning arthroscopy skills. Despite significant research, one drawback often outlined is the difficulty in distinguishing performance levels (Construct Validity) in experienced surgeons. Therefore, it seems adequate to search new methods of performance measurements using probe trajectories instead of commonly used metrics.

Offline identification of surgical deviations in laparoscopic rectopexy.

Objective: According to a meta-analysis of 7 studies, the median number of patients with at least one adverse event during the surgery is 14.4%, and a third of those adverse events were preventable. The occurrence of adverse events forces surgeons to implement corrective strategies and, thus, deviate from the standard surgical process.

Assessment of surgical skills by using surgical navigation in robot-assisted partial nephrectomy.

Purpose: To assess surgical skills in robot-assisted partial nephrectomy (RAPN) with and without surgical navigation (SN).

Methods: We employed an SN system that synchronizes the real-time endoscopic image with a virtual reality three-dimensional (3D) model for RAPN and evaluated the skills of two expert surgeons with regard to the identification and dissection of the renal artery (non-SN group, n = 21 [first surgeon n = 9, second surgeon n = 12]; SN group, n = 32 [first surgeon n = 11, second surgeon n = 21]). We converted all movements of the robotic forceps during RAPN into a dedicated vocabulary.

Surgical motion analysis using discriminative interpretable patterns.

Objective: The analysis of surgical motion has received a growing interest with the development of devices allowing their automatic capture. In this context, the use of advanced surgical training systems makes an automated assessment of surgical trainee possible. Automatic and quantitative evaluation of surgical skills is a very important step in improving surgical patient care.

Sequential surgical signatures in micro-suturing task.

Purpose: Surgical processes are generally only studied by identifying differences in populations such as participants or level of expertise. But the similarity between this population is also important in understanding the process. We therefore proposed to study these two aspects.

Distinguishing surgical behavior by sequential pattern discovery.

Objective: Each surgical procedure is unique due to patient's and also surgeon's particularities. In this study, we propose a new approach to distinguish surgical behaviors between surgical sites, levels of expertise and individual surgeons thanks to a pattern discovery method.

Methods: The developed approach aims to distinguish surgical behaviors based on shared longest frequent sequential patterns between surgical process models.

Automatic data-driven real-time segmentation and recognition of surgical workflow.

Purpose: With the intention of extending the perception and action of surgical staff inside the operating room, the medical community has expressed a growing interest towards context-aware systems. Requiring an accurate identification of the surgical workflow, such systems make use of data from a diverse set of available sensors. In this paper, we propose a fully data-driven and real-time method for segmentation and recognition of surgical phases using a combination of video data and instrument usage signals, exploiting no prior knowledge.