title: Force feedback in a piezoelectric linear actuator for neurosurgery.
abstract: BACKGROUND
  Force feedback in robotic minimally invasive surgery allows the human operator to manipulate tissues as if his/her hands were in contact with the patient organs. A force sensor mounted on the probe raises problems with sterilization of the overall surgical tool. Also, the use of off-axis gauges introduces a moment that increases the friction force on the bearing, which can easily mask off the signal, given the small force to be measured.
  
  
  METHODS
  This work aims at designing and testing two methods for estimating the resistance to the advancement (force) experienced by a standard probe for brain biopsies within a brain-like material. The further goal is to provide a neurosurgeon using a master-slave tele-operated driver with direct feedback on the tissue mechanical characteristics. Two possible sensing methods, in-axis strain gauge force sensor and position-position error (control-based method), were implemented and tested, both aimed at device miniaturization. The analysis carried out was aimed at fulfilment of the psychophysics requirements for force detection and delay tolerance, also taking into account safety, which is directly related to the last two issues. Controller parameters definition is addressed and consideration is given to development of the device with integration of a haptic interface.
  
  
  RESULTS
  Results show better performance of the control-based method (RMSE < 0.1 N), which is also best for reliability, sterilizability, and material dimensions for the application addressed.
  
  
  CONCLUSIONS
  The control-based method developed for force estimation is compatible with the neurosurgical application and is also capable of measuring tissue resistance without any additional sensors. Force feedback in minimally invasive surgery allows the human operator to manipulate tissues as if his/her hands were in contact with the patient organs.
authors.affiliation: Politecnico di Milano, Bioengineering Department, NearLab, Milano, Italy. danilo.delorenzo@mail.polimi.it.
authors.forename: Danilo
authors.initials: D
authors.lastname: De Lorenzo
authors.forename: Elena
authors.initials: E
authors.lastname: De Momi
authors.forename: Ilya
authors.initials: I
authors.lastname: Dyagilev
authors.forename: Rudy
authors.initials: R
authors.lastname: Manganelli
authors.forename: Alessandro
authors.initials: A
authors.lastname: Formaglio
authors.forename: Domenico
authors.initials: D
authors.lastname: Prattichizzo
authors.forename: Moshe
authors.initials: M
authors.lastname: Shoham
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Ferrigno
mesh_terms: D001706:Biopsy / Q000295:instrumentation / Q000379:methods; D001921:Brain / Q000473:pathology; D003198:Computer Simulation; D004867:Equipment Design; D005246:Feedback; D006801:Humans; D008866:Microsurgery / Q000295:instrumentation; D019060:Minimally Invasive Surgical Procedures; D019635:Neurosurgical Procedures / Q000295:instrumentation*; D011601:Psychophysics; D015203:Reproducibility of Results; D065287:Robotic Surgical Procedures / Q000295:instrumentation*; D013314:Stress, Mechanical; D025321:Surgery, Computer-Assisted / Q000295:instrumentation; D014584:User-Computer Interface