This work introduces an anatomy-based simulator of pulmonary vein integrated with soft textile sensing. Sensor data can be processed to extract a simple metric related to the vessel strain and this information was proven to objectively discriminate medical users with heterogeneous levels of expertise. This feature (construct validity) plays a relevant role in training and education, as it can be used to assess when the trainee has learnt how to master a certain skill. The possibility to assess skills
by using a sensor makes the evaluation totally objective, as well as independent from the presence of a proctor. In addition to skill assessment, sensor data can be used to provide a warning feedback to the trainee (e.g., using a buzzer). A strain-based feedback could optimize learning the robot-assisted manipulation of vascular structures (where haptic feedback is usually missing) by teaching the maximum strain that can be applied.