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.
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: Marco Aggravi; Elena De Momi; Francesco DiMeco; Francesco Cardinale; Giuseppe Casaceli; Marco Riva; Giancarlo Ferrigno; Domenico Prattichizzo Journal: Med Biol Eng Comput Date: 2015-12-31 Impact factor: 2.602
Authors: Danilo De Lorenzo; Elena De Momi; Lorenzo Conti; Emiliano Votta; Marco Riva; Enrica Fava; Lorenzo Bello; Giancarlo Ferrigno Journal: Med Biol Eng Comput Date: 2012-12-02 Impact factor: 2.602
Authors: P Mazzone; P Arena; L Cantelli; G Spampinato; S Sposato; S Cozzolino; P Demarinis; G Muscato Journal: J Neural Transm (Vienna) Date: 2016-05-19 Impact factor: 3.575