title: 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.
authors.affiliation: School of Automation & Electrical Engineering, University of Science and Technology, Beijing, People's Republic of China.
authors.forename: Tianyang
authors.initials: T
authors.lastname: Cao
authors.forename: Xisheng
authors.initials: X
authors.lastname: Li
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Gao
authors.forename: Guodong
authors.initials: G
authors.lastname: Feng
authors.forename: Peng
authors.initials: P
authors.lastname: Shen
mesh_terms: D000465:Algorithms; D001842:Bone and Bones / Q000601:surgery*; D004423:Ear / Q000601:surgery*; D004574:Electromagnetic Fields; D004867:Equipment Design; D006801:Humans; D008422:Materials Testing; D015233:Models, Statistical; D012371:Robotics / Q000295:instrumentation / Q000379:methods*; D012984:Software; D025321:Surgery, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D019415:Torque