Abstract: Embodiments of the present disclosure include a method for determining a shape of a catheter. The method can include receiving a plurality of impedance measurements from a plurality of electrodes disposed on a flexible tip portion of the catheter. The method can include receiving a magnetic position measurement from a magnetic position sensor disposed on a shaft of the catheter. The method can include determining a relationship between each of the plurality of electrodes disposed on the flexible tip portion of the catheter, based on the impedance measurements received from the plurality of electrodes. The method can include predicting a shape of the flexible tip portion of the catheter, based on the determined relationship between each of the plurality of electrodes disposed on the flexible tip portion of the catheter. The method can include determining a shape of the catheter, based on the magnetic position measurement and the predicted shape of the flexible tip portion.

Abstract: Embodiments herein relate to identifying a learning engagement state of a learner. A computing platform with one or more processors running modules may receive indications of interactions of a learner with an educational program as well as indications of physical responses of the learner collected substantially simultaneously as the learner interacts with the educational program. A current learning engagement state of the learner may be identified based at least in part on the received indications by using an artificial neural network associated that is calibrated to the learner. The artificial neural network may be trained and updated in part by human observation and learner self-reporting of the learner's current learning engagement state.