TY  - JOUR
T1  - Estimation of the stapes-bone thickness in the stapedotomy surgical procedure using a machine-learning technique.
JF  - IEEE Transactions on information technology in biomedicine
A1  - Kaburlasos, V.G
LA  - English
UL  - https://tuklas.up.edu.ph/Record/UP-99796217609548474
AB  - Stapedotomy is a surgical procedure aimed at the treatment of hearing impairment due to otosclerosis. The treatment consists of drilling a hole through the stapes bone in the inner ear in order to insert a prosthesis. Safety precautions require knowledge of the nonmeasurable stapes thickness. The technical goal has been the design of high-level controls for an intelligent mechatronics drilling tool in order to enable the estimation of stapes thickness from measurable drilling data. The goal has been met by learning a map between drilling features, hence no model of the physical system has been necessary. Learning has been achieved as explained in this paper by a scheme, namely the d-σ Fuzzy Lattice Neurocomputing (dσ-FLN) scheme for classification, within the framework of fuzzy lattices. The successful application of the dσ-FLN scheme is demonstrated in estimating the thickness of a stapes bone "on-line" using drilling data obtained experimentally in the laboratory.
KW  - Classification.
KW  - D-/spl sigma/ Fuzzy Lattice Neurocomputing scheme.
KW  - Hearing impairment treatment.
KW  - High-level controls.
KW  - Hole drilling.
KW  - Inner ear.
KW  - Intelligent mechatronics drilling tool.
KW  - Machine learning technique.
KW  - Measurable drilling data.
KW  - Nonmeasurable stapes thickness.
KW  - Otosclerosis.
KW  - Prosthesis insertion.
KW  - Safety precautions.
KW  - Stapedotomy surgical procedure.
KW  - Stapes bone thickness estimation.
ER  -