Measurement, analysis, and display of haptic signals during surgical cutting

  • Authors:
  • Stephanie Greenish;Vincent Hayward;Vanessa Chial;Allison Okamura;Thomas Steffen

  • Affiliations:
  • Center for Intelligent Machines, McGill University, 3480 University Street, Montréal, Qc, Canada;Center for Intelligent Machines, McGill University, 3480 University Street, Montréal, Qc, Canada;Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD;Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD;Orthopaedic Research Laboratory, Royal Victoria Hospital, Montréal, Québec, Canada

  • Venue:
  • Presence: Teleoperators and Virtual Environments
  • Year:
  • 2002

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Abstract

The forces experienced while surgically cutting anatomical tissues from a sheep and two rats were investigated for three scissor types. Data were collected in situ using instrumented Mayo, Metzenbaum anc Iris scissors immediately after death to minimize postmortem effects. The force-position relationship, the frequency components presens in the signal, the significance of the cutting rate. and other invariant properties were investigated after segmentation of the data into distinct task phases. Measurements were found to be independent of the cutting speed for Mayo and Metzenbaum scissors, but the results for Iris scissors were inconclusive. Sensitivity to cutting tissues longitudinally or transversely depended on both the tissue and on the scissor type. Data from cutting three tissues (rat skin, liver, and tendon) with Metzenbaum scissors as well as blank runs were processed and displayed as haptic recordings through a custom-designed haptic interface. Experiments demonstrated that human subjects could identify tissues with similar accuracy when performing a real or simulated cutting task. The use of haptic recordings to generate the simulations was simple and efficient, but it lacked flexibility because only the information obtained during data acquisition could be displayed. Future experiments should account for the user grip, tissue thickness, tissue moisture content, hand orientation, and innate scissor dynamics. A database of the collected signals has been created on the Internet for public use at www.cim.mcgill.ca/~haptic/tissue/data.html.