Learning a linear association of drilling profiles in stapedotomy surgery

Abstract

The two-level fuzzy-lattice (2L-FL) learning scheme is introduced for application on an intelligent surgical (mechatronic) drill in the stapedotomy surgical procedure in the ear. The 2L-FL scheme learned from past cases to evaluate pointedly the thickness of a stapes bone using a force/torque pair of drilling profiles. Hence it is possible, in principle, to drill safely a hole through supple stapes by retracting automatically the drill upon bone breakthrough. The 2L-FL scheme was applied on two different partly ordered sets defined on a set of square matrices mapping features of two different data profiles to one another. Results are presented comparatively on experimental drilling data. The authors also discuss extension of their techniques to other surgical and industrial applications especially ones involving fusion of disparate sensory data where effective learning could compensate for the lack of accurate analytical models.