3D Printed heterogeneously integrated sensors embedded in Anatomical training models

Despite the large number of procedural simulation models currently available, there is a definite need for low cost anatomical training models with integrated sensors capable of recording the location and pressure measurements of a user"s performance in training of cuts, and sutures. A paradigm shift in medical training is possible if sensors can either be fabricated independently and embedded into the model, or ideally incorporated in the fabrication process directly such that the user"s manipulation of the mode are tracked and recorded. Unfortunately, current synthetic models require validation and most still need an expert to review the novice"s actions subjectively. In an ideal system, extensive data on the performance of the user could be fed into realistic overall systemic models. In this work we propose a method of incorporating force sensors heterogeneously with synthetic tissue by using a multi-material 3D printing platform. This approach is expected to enable low cost sensing that can be integrated with additional sensors in a simulator to accurately track the performance of a student without requiring an instructor to watch.