Enabling non-engineers to use engineering tools: introducing product development to pupils using knowledge-integrating systems

Many engineering tasks are supported by tools based on innovative technologies. Powerful tools for computer aided design, simulations or programming permit a wide range of possibilities for engineers in solving complex problems. However, using these tools commonly requires extensive training or specific skills. Specialized systems that enable tool and technology usage could support novices in solving engineering tasks using embedded knowledge, lowering the hurdle of expertise required for operation. In the presented case study, knowledge-integrating systems inspired by knowledge-based engineering were developed to allow pupils to solve an engineering challenge without existing skills or prior training. To provide a realistic application context, a teaching module was developed, introducing high school students to product engineering in the form of a conceive-design-implement-operate experience with the learning goal to engage them in the STEM field. Solving the included engineering challenge required the creation, test and iteration of designs for laser cut and additive manufacturing, and code processing sensor signals for motor actuation. To evaluate the knowledge-integrating systems in their use qualitatively, a trial run was conducted. Participants were enabled to fulfil basic product engineering tasks and expressed engagement in product development and overall satisfaction. The module’s key element is an educational exoskeleton that can be controlled by electromyography signals. It is modified to eventually support a fictional character suffering from monoplegia. The module was realized accompanying the CYBATHLON, a championship for people with physical disabilities in solving everyday tasks assisted by state-of-the-art technical systems

Enabling non-engineers to use engineering tools: introducing product development to pupils using knowledge-integrating systems

Many engineering tasks are supported by tools based on innovative technologies. Powerful tools for computer aided design, simulations or programming permit a wide range of possibilities for engineers in solving complex problems. However, using these tools commonly requires extensive training or specific skills. Specialized systems that enable tool and technology usage could support novices in solving engineering tasks using embedded knowledge, lowering the hurdle of expertise required for operation. In the presented case study, knowledge-integrating systems inspired by knowledge-based engineering were developed to allow pupils to solve an engineering challenge without existing skills or prior training. To provide a realistic application context, a teaching module was developed, introducing high school students to product engineering in the form of a conceive-design-implement-operate experience with the learning goal to engage them in the STEM field. Solving the included engineering challenge required the creation, test and iteration of designs for laser cut and additive manufacturing, and code processing sensor signals for motor actuation. To evaluate the knowledge-integrating systems in their use qualitatively, a trial run was conducted. Participants were enabled to fulfil basic product engineering tasks and expressed engagement in product development and overall satisfaction. The module’s key element is an educational exoskeleton that can be controlled by electromyography signals. It is modified to eventually support a fictional character suffering from monoplegia. The module was realized accompanying the CYBATHLON, a championship for people with physical disabilities in solving everyday tasks assisted by state-of-the-art technical systems.ISSN:2212-827

Automated tracheal intubation in an airway manikin using a robotic endoscope: a proof of concept study

ISSN:0003-2409ISSN:1365-204

REALITI: A Robotic Endoscope Automated via Laryngeal Imaging for Tracheal Intubation

Tracheal intubation is considered the gold standard to secure the airway of patients in need of respiratory assistance, yet this procedure relies on the dexterity and experience of the physician to correctly place a tracheal tube into the patient’s trachea. Such a complex procedure may greatly benefit from robotic assistance in order to make the intubation safer and more efficient. We developed the first device to provide such assistance, the REALITI, which stands for Robotic Endoscope Automated via Laryngeal Imaging for Tracheal Intubation. This device allies the automated detection of key anatomical features in an endoscopic image to the robotic steering toward the recognized features in the task of guiding the tracheal tube into its correct position. The pre-clinical prototype presented in this paper has been developed to perform in vitro tracheal inbutation on a standard airway management training manikin. We performed a robust detection of anatomical features to steer the endoscope in a visual servoing fashion. Our prototype has been successfully used to perform automated and manual insertions into the trachea of an airway manikin

REALITI: A Robotic Endoscope Automated via Laryngeal Imaging for Tracheal Intubation

Tracheal intubation is considered the gold standard to secure the airway of patients in need of respiratory assistance, yet this procedure relies on the dexterity and experience of the physician to correctly place a tracheal tube into the patient's trachea. Such a complex procedure may greatly benefit from robotic assistance in order to make the intubation safer and more efficient. We developed the first device to provide such assistance, the REALITI, which stands for Robotic Endoscope Automated via Laryngeal Imaging for Tracheal Intubation. This device allies the automated detection of key anatomical features in an endoscopic image to the robotic steering toward the recognized features in the task of guiding the tracheal tube into its correct position. The pre-clinical prototype presented in this paper has been developed to perform in vitro tracheal inbutation on a standard airway management training manikin. We performed a robust detection of anatomical features to steer the endoscope in a visual servoing fashion. Our prototype has been successfully used to perform automated and manual insertions into the trachea of an airway manikin