A portable soft robotic patient simulator for training physical examination skills to improve early diagnosis accuracy

Context and challenges: Physical examinations can contribute up to 20% of the data necessary for the diagnosis and management of a patient. Since this phase of diagnosis involves the judgement of the physician based on touch, visual, and auditory information from a wide range of patients, the reliability of diagnosis heavily depends on the proficiency of medical professionals, which can vary. This inconsistency can lead to Missed Diagnosis Opportunities (MDOs) and errors, contributing to clinical negligence claims which cost the NHS over £2 billion annually . Unfortunately, students have limited opportunities to practice physical examination techniques on real patients and rely on mannequins or humans with no pathologies for learning. There are limitations to present a wide range of scenarios using these methods. Potential applications and benefits: We are developing an innovative interactive medical simulation system designed to help medical students to learn and practice crucial physical examination skills, particularly palpation. This portable and accessible simulator can give students exposure to a variety of pathologies and patient scenarios before they begin clinical practice, reducing the need to "learn on the job." The medical simulation system is made of two components: a soft robotic haptic-enabled computer mouse (based on ‘Physical Pixel’ concept), and reactive ‘Virtual Patient’ software. The novel and beneficial aspects include: The ‘Physical Pixel’ concept which involves mimicking the physical properties of the abdomen at the location of the cursor on the Virtual Patient, enabling students to engage in realistic, hands-on training using a device smaller than the exploration area. Combined with the Virtual Patient which provides real time indentations and force reactions, a strong correlation to the real palpation scenario is created. Our new approach to haptic technology offers a direct, tactile experience by physically altering the device’s properties instead of actively simulating touch effects through vibration or restraint, allowing users to experience barehand interaction with the patient phantom. Real time stiffness control is achieved through novel, patentable mechanisms. The mixed-mode hardware and software approach offers versatility in pathologies and patient types, tuneability to meet all teaching needs, decreased costs by using standard computer screens, easier storage, and objective feedback on performance which is a rare and useful feature in this type of learning. The data collected during use is analysed to provide users with a detailed breakdown of their palpation performance, and this large-scale data collection from all users can be used to understand more about how physicians palpate in general and continuously improve the training techniques. Aims and Objectives: To date, we have created multiple working prototypes and completed initial tests with medical students to evaluate how well they adapt to and learn a simplified palpation method with the simulator. However, our crucial gap in development is validation that our technology is able to present real pathologies for a physician to diagnose with their existing palpation technique and knowledge. To achieve this, we plan to conduct three design iterations. Each iteration will be tested by medical professionals to determine whether their diagnoses align with the programmed scenarios for various pathologies and symptoms, including tenderness, rigidity, muscle guarding, masses (such as cysts and hernias). This 8 month project will allow us to move forward confidently with our product, ready for final testing and commercialisation.