A method for identifying otological drill milling through bone tissue wall

Abstract

BACKGROUND: Otological drill milling through the bone tissue wall is a common milling fault in ear surgery. This paper presents a method for identifying milling faults and improving operation safety. METHODS: Force and current sensors are used. According to a DC motor model and a cutting force model, the features of the milling process were analysed and a dynamic model was established. The dynamic model could extract the characteristic curve of a milling fault and the phase difference between the current and force signals. An adaptive filter was designed to fuse the phase and amplitude of signals to suppress interference in the characteristic curve. According to the filtering result, milling states can be identified by a rule base. RESULTS: Five surgeons carried out experiments on calvarian bone. The average recognition rate of milling faults was 90%. Only 1% of normal millings were identified as milling faults. CONCLUSIONS: This method could be adapted to different surgeons and identify milling faults exactly.