Purpose: There is very little documented evidence regarding the training of paediatric surgeons in South Africa since its inception as a formal speciality in 2007. This study aims to assess South African paediatric surgical trainees' perspectives regarding their training. Methods: A prospective study was conducted via an emailed electronic survey. The sample population included all current paediatric surgical trainees in South Africa. The questionnaire covered the trainees' demographics, exposure to different aspects of paediatric surgery, extent of after-hours clinical service, self - reported surgical competency and consultant supervision. Results: Forty one (95%) out of 43 trainees responded to the survey with 29 (71%) being female. Reported training deficits included lack of exposure to burn care in 12 trainees (30%), no urology exposure in 8 (20%), no paediatric trauma or minimally invasive surgery exposure in 6 (15%). Eighteen trainees (44%) reportedly worked more than 65 hours per week with clinical responsibilities being the biggest hindrance to attending academic teaching. Trainees were more comfortable performing open procedures compared to laparoscopic but most respondents felt adequately supervised. Conclusion: There exists a significant heterogeneity amongst the different training institutions with protected academic time and exposure to burns, urology and minimally invasive surgery remaining major obstacles in training.

Minimally Invasive Surgery (MIS) is a surgical technique involving small incisions performed by an endoscope and several long, thin instruments. Because of its minimally invasive nature, MIS minimizes complications and speeds up recovery time compared to the traditional surgery. Unfortunately, from a surgeon's perspective, MIS is much more challenging than conventional surgery. Because the limited vision and sensing feedbacks, MIS a difficult skill for medical students and residents to master.There has been some research on the effectiveness of different kinds of training and guidance. Surgical simulation is increasingly perceived as a valuable addition to traditional medical training methods, although most existing simulators have limitations stemming from either a lack of objective performance assessment or an insufficient relation to the operating room reality.The objective of this research is to design and realize a novel prototype that advances the state of the art in surgical training, assessment, and guidance for MIS. The prototype features micro-sensors embedded into the instruments employed for simulation training. The system provides multiple training scenarios, a high fidelity training environment, repeatable, structured exercises, and objective performance assessment capabilities.The proposed Situational Awareness Enhancing System (SAES) uses a unified framework incorporating perception, comprehension, and projection software modules that provide feedback during the exercises and enable evaluation of the training procedure.A multiple sensor data fusion method was developed to help surgeons efficiently acquire information in real time. The output, "Hybridview", is produced by fusing the information from digital camera and magnetic position sensors, and shows an overlay of the positions of organs and objects with the trajectory of instruments. An intelligent inference engine was designed to formulate an objective standard based on the expertise of senior surgeons and to provide an accurate scoring method. A multi-level fuzzy inference engine and new performance metrics were implemented.To demonstrate the feasibility of the proposed training system, numerous experiments were conducted. The results show that the situational awareness training system for MIS is useful and efficient.

<p>The advancement of robotic-assisted surgery (RAS) has revolutionized the field by enabling surgeons to perform intricate procedures with enhanced precision, improved depth perception, and more precise control. Despite these advancements, current RAS systems still rely on teleoperation, where surgeons control the robots remotely. The complexity of the master-slave control mechanism, along with the technical challenges involved, can impose significant mental workloads on surgeons. As excessive mental workload (MWL) can adversely affect performance and increase the likelihood of errors, addressing operator mental overload has become crucial for successful operation in RAS. To tackle this problem, there has been increased interest in developing robots that can provide operators with varying levels of assistance based on their MWL (i.e., adaptive system) during task execution. However, the research in this area is notably limited, primarily due to two key factors: the absence of a real-time MWL assessment framework and the lack of effective intervention strategies to mitigate MWL in RAS.</p> <p>This Ph.D. dissertation aims to fill these gaps by designing the adaptive system in RAS and exploring its impact on surgical task performance. The dissertation comprises three studies. The first study demonstrated the feasibility of the adaptive system in RAS by introducing an MWL-triggered semi-autonomous suction tool as a proof-of-concept. Building upon the insights gained from the first study, the second study focused on enhancing the adaptive system's adaptability to more complex RAS tasks. In particular, the second study proposed a task-independent MWL model that had potential to be applied to various RAS tasks. Additionally, more intelligent interventions were investigated. Furthermore, the third study aimed to investigate the benefits of adaptive system in RAS training by introducing a personalized and adaptive training program based on human MWL profile. The findings of this dissertation revealed evidence supporting the effectiveness of the adaptive system in moderating subjects’ MWL, and its potential in enhancing task performance in RAS. This dissertation highlights the potential of incorporating adaptive systems into future RAS platforms, so that to provide valuable support and assistance to surgeons during critical moments and facilitate surgical training by identifying and addressing the specific needs of surgeons.</p>

Le système perceptif d’un chirurgien doit s’adapter aux contraintes multisensorielles liées à la chirurgie guidée par l’image. Trois expériences sont conçues pour explorer ces contraintes visuelles et haptiques pour l’apprentissage guidé par l’image. Les résultats montrent que les sujets sont plus rapides et plus précis avec une vision directe. La stéréoscopie 3D n’améliore pas les performances des débutants complets. En réalité virtuelle, la variation de la longueur, largeur, position et complexité de l'objet affecte les performances motrices. La force de préhension appliquée sur un système robotique chirurgical dépend de l'expérience de l'utilisateur. En conclusion, le temps et la précision sont importants, mais la précision doit rester une priorité pour un apprenti. L'homogénéité des groupes d'étude est important pour la recherche sur la formation chirurgicale. Les résultats ont un impact direct sur le suivi des compétences individuelles pour les applications guidées par l'image. / Perceptual system of a surgeon must adapt to conditions of multisensorial constrains regard to planning, control, and execution of the image-guided surgical operations. Three experimental setups are designed to explore these visual and haptic constraints in the image-guided training. Results show that subjects are faster and more precise with direct vision compared to image guidance. Stereoscopic 3D viewing does not represent a performance advantage for complete beginners. In virtual reality, variation in object length, width, position, and complexity affect the motor performance. Applied grip force on a surgical robot system depends on the user experience level. In conclusion, both time and precision matter critically, but trainee gets as precise as possible before getting faster should be a priority. Study group homogeneity and background play key role in surgical training research. The findings have direct implications for individual skill monitoring for image-guided applications.

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