Abstract
In the realm of medicine, fundamental and effective education is of crucial importance due to the complexity of the human body. It plays a pivotal role in ensuring patient safety, particularly in the context of complex surgical procedures. Surgical simulations offer an ethically sound, risk-free environment where prospective surgeons can practice and evaluate intricate procedures. Despite the numerous benefits of simulation-based training methods, surgical simulation is not yet commonplace in the education of young medical professionals due to often lacking usability and prohibitive costs.
This dissertation introduces an innovative approach to surgical simulation, focusing on the application of intelligent artificial soft tissue in hybrid surgical simulators. Hybrid simulators employ both physical and virtual components to ensure an optimal fusion of haptic feedback, visual appearance, and digital evaluability of a simulated operation. The intelligent artificial soft tissue aims to provide a discreet and cost-effective link between the physical and virtual worlds, facilitating their synchronization. This entails implementing both sensory and actuator functionalities to maximize design flexibility when creating physical patient phantoms. The intelligent tissue structures can be seamlessly integrated into haptically adapted synthetic tissue substitutes to mimic the tactile sensation surgeons experience when manipulating the physical patient phantom as realistically as possible. Digital evaluability forms a key element in assessing the performed simulations, as it allows for reproducibly objective statements regarding the quality of a trained procedure.
Initially, a comprehensive electromechanical characterization of the sensor material, a mixture of carbon black and silicone, is presented. Based on this, an interface module for easy evaluation of various sensor structures is introduced. This enables universally applicable, sensor material-optimized evaluation of external influences on corresponding detectors. Enhanced with soft, hydraulic actuators, these sensors form an ideal basic building block for surgical simulators that can actively interact with the simulation environment as needed. Demonstrations of feasibility concerning organs such as the brain or heart, as well as muscles or other types of tissue, are also discussed. Furthermore, the integration of this technology into a functional hybrid surgical simulator for training the implantation of electrodes for a laryngeal pacemaker is examined. This application example clearly illustrates the efficiency and compactness of the proposed solution. In addition to surgical simulators, a method for biosignal analysis of electrocardiogram data is presented, enabling the integration of patient-specific heart rhythms or arrhythmias into a simulation, or alternatively, allowing analytical conclusions about the mental stress level of the training surgeons. This can improve both the realism of a training intervention and the evaluability of trainee proficiency. Moreover, the integration of patient data paves the way for personalized, preoperative training.
This dissertation introduces an innovative approach to surgical simulation, focusing on the application of intelligent artificial soft tissue in hybrid surgical simulators. Hybrid simulators employ both physical and virtual components to ensure an optimal fusion of haptic feedback, visual appearance, and digital evaluability of a simulated operation. The intelligent artificial soft tissue aims to provide a discreet and cost-effective link between the physical and virtual worlds, facilitating their synchronization. This entails implementing both sensory and actuator functionalities to maximize design flexibility when creating physical patient phantoms. The intelligent tissue structures can be seamlessly integrated into haptically adapted synthetic tissue substitutes to mimic the tactile sensation surgeons experience when manipulating the physical patient phantom as realistically as possible. Digital evaluability forms a key element in assessing the performed simulations, as it allows for reproducibly objective statements regarding the quality of a trained procedure.
Initially, a comprehensive electromechanical characterization of the sensor material, a mixture of carbon black and silicone, is presented. Based on this, an interface module for easy evaluation of various sensor structures is introduced. This enables universally applicable, sensor material-optimized evaluation of external influences on corresponding detectors. Enhanced with soft, hydraulic actuators, these sensors form an ideal basic building block for surgical simulators that can actively interact with the simulation environment as needed. Demonstrations of feasibility concerning organs such as the brain or heart, as well as muscles or other types of tissue, are also discussed. Furthermore, the integration of this technology into a functional hybrid surgical simulator for training the implantation of electrodes for a laryngeal pacemaker is examined. This application example clearly illustrates the efficiency and compactness of the proposed solution. In addition to surgical simulators, a method for biosignal analysis of electrocardiogram data is presented, enabling the integration of patient-specific heart rhythms or arrhythmias into a simulation, or alternatively, allowing analytical conclusions about the mental stress level of the training surgeons. This can improve both the realism of a training intervention and the evaluability of trainee proficiency. Moreover, the integration of patient data paves the way for personalized, preoperative training.
Original language | English (American) |
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Publication status | Published - Sept 2024 |