Literature DB >> 26718558

Hand-tool-tissue interaction forces in neurosurgery for haptic rendering.

Marco Aggravi1, Elena De Momi2, Francesco DiMeco3, Francesco Cardinale4, Giuseppe Casaceli4, Marco Riva5, Giancarlo Ferrigno2, Domenico Prattichizzo6.   

Abstract

Haptics provides sensory stimuli that represent the interaction with a virtual or tele-manipulated object, and it is considered a valuable navigation and manipulation tool during tele-operated surgical procedures. Haptic feedback can be provided to the user via cutaneous information and kinesthetic feedback. Sensory subtraction removes the kinesthetic component of the haptic feedback, having only the cutaneous component provided to the user. Such a technique guarantees a stable haptic feedback loop, while it keeps the transparency of the tele-operation system high, which means that the system faithfully replicates and render back the user's directives. This work focuses on checking whether the interaction forces during a bench model neurosurgery operation can lie in the solely cutaneous perception of the human finger pads. If this assumption is found true, it would be possible to exploit sensory subtraction techniques for providing surgeons with feedback from neurosurgery. We measured the forces exerted to surgical tools by three neurosurgeons performing typical actions on a brain phantom, using contact force sensors, while the forces exerted by the tools to the phantom tissue were recorded using a load cell placed under the brain phantom box. The measured surgeon-tool contact forces were 0.01-3.49 N for the thumb and 0.01-6.6 N for index and middle finger, whereas the measured tool-tissue interaction forces were from six to 11 times smaller than the contact forces, i.e., 0.01-0.59 N. The measurements for the contact forces fit the range of the cutaneous sensitivity for the human finger pad; thus, we can say that, in a tele-operated robotic neurosurgery scenario, it would possible to render forces at the fingertip level by conveying haptic cues solely through the cutaneous channel of the surgeon's finger pads. This approach would allow high transparency and high stability of the haptic feedback loop in a tele-operation system.

Entities:  

Keywords:  Brain phantom forces; Contact forces; Haptic rendering; Neurosurgery

Mesh:

Year:  2015        PMID: 26718558     DOI: 10.1007/s11517-015-1439-8

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  22 in total

1.  Mechanical properties of brain tissue in-vivo: experiment and computer simulation.

Authors:  K Miller; K Chinzei; G Orssengo; P Bednarz
Journal:  J Biomech       Date:  2000-11       Impact factor: 2.712

Review 2.  Haptic rendering: introductory concepts.

Authors:  Kenneth Salisbury; Francois Conti; Federico Barbagli
Journal:  IEEE Comput Graph Appl       Date:  2004 Mar-Apr       Impact factor: 2.088

3.  Intraoperative forces and moments analysis on patient head clamp during awake brain surgery.

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

4.  The evolution of neuroArm.

Authors:  Garnette R Sutherland; Stefan Wolfsberger; Sanju Lama; Kourosh Zarei-nia
Journal:  Neurosurgery       Date:  2013-01       Impact factor: 4.654

5.  In-vivo implant mechanics of flexible, silicon-based ACREO microelectrode arrays in rat cerebral cortex.

Authors:  Winnie Jensen; Ken Yoshida; Ulrich G Hofmann
Journal:  IEEE Trans Biomed Eng       Date:  2006-05       Impact factor: 4.538

6.  Measurement of the force required to move a neurosurgical probe through in vivo human brain tissue.

Authors:  M A Howard; B A Abkes; M C Ollendieck; M D Noh; R C Ritter; G T Gillies
Journal:  IEEE Trans Biomed Eng       Date:  1999-07       Impact factor: 4.538

7.  A robotic system to train activities of daily living in a virtual environment.

Authors:  Marco Guidali; Alexander Duschau-Wicke; Simon Broggi; Verena Klamroth-Marganska; Tobias Nef; Robert Riener
Journal:  Med Biol Eng Comput       Date:  2011-07-28       Impact factor: 2.602

8.  Force feedback in a piezoelectric linear actuator for neurosurgery.

Authors:  Danilo De Lorenzo; Elena De Momi; Ilya Dyagilev; Rudy Manganelli; Alessandro Formaglio; Domenico Prattichizzo; Moshe Shoham; Giancarlo Ferrigno
Journal:  Int J Med Robot       Date:  2011-04-28       Impact factor: 2.547

9.  Markov modeling of minimally invasive surgery based on tool/tissue interaction and force/torque signatures for evaluating surgical skills.

Authors:  J Rosen; B Hannaford; C G Richards; M N Sinanan
Journal:  IEEE Trans Biomed Eng       Date:  2001-05       Impact factor: 4.538

10.  Forces exerted during microneurosurgery: a cadaver study.

Authors:  Hani J Marcus; Kourosh Zareinia; Liu Shi Gan; Fang Wei Yang; Sanju Lama; Guang-Zhong Yang; Garnette R Sutherland
Journal:  Int J Med Robot       Date:  2014-01-16       Impact factor: 2.547

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  3 in total

1.  The Challenge of Dental Education After COVID-19 Pandemic - Present and Future Innovation Study Design.

Authors:  Miguel Pais Clemente; André Moreira; João Correia Pinto; José Manuel Amarante; Joaquim Mendes
Journal:  Inquiry       Date:  2021 Jan-Dec       Impact factor: 1.730

Review 2.  Tool-tissue forces in surgery: A systematic review.

Authors:  Aida Kafai Golahmadi; Danyal Z Khan; George P Mylonas; Hani J Marcus
Journal:  Ann Med Surg (Lond)       Date:  2021-03-31

3.  Soft Robotic Deployable Origami Actuators for Neurosurgical Brain Retraction.

Authors:  Tomas Amadeo; Daniel Van Lewen; Taylor Janke; Tommaso Ranzani; Anand Devaiah; Urvashi Upadhyay; Sheila Russo
Journal:  Front Robot AI       Date:  2022-01-14
  3 in total

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