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Quantifying force and positional frequency bands in neurosurgical tasks.

Yaser Maddahi1, Ahmad Ghasemloonia1, Kourosh Zareinia1

  • 1Project neuroArm, Department of Clinical Neuroscience and the Hotchkiss Brain Institute, University of Calgary, 1C58-HRIC, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada.

Journal of Robotic Surgery
|February 26, 2016
PubMed
Summary

This study quantifies mechanical motion and forces during neurosurgical tasks to inform the design of MR-compatible haptic controllers for virtual surgery within MRI scanners.

Keywords:
Frequency bandwidthHaptic hand-controllerInteraction forceNeurosurgerySpectral analysisWorkspace

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Area of Science:

  • Neurosurgery
  • Medical Device Design
  • Human-Computer Interaction

Background:

  • Designing MR-compatible haptic controllers is crucial for enabling virtual neurosurgical procedures within functional MRI (fMRI) environments.
  • Understanding the mechanical demands of neurosurgical tasks is essential for creating effective haptic feedback systems.

Purpose of the Study:

  • To determine the design requirements for an MR-compatible haptic hand-controller.
  • To measure motion and force components during simulated neurosurgical tasks.

Main Methods:

  • A bipolar forceps equipped with tracking and force sensors was used to measure tool position, orientation, and interaction forces on a cadaveric brain.
  • Analysis focused on identifying working frequency bands and peak forces during simulated neurosurgical tasks.

Main Results:

  • Working frequency bands for position, rotation, and force were identified as 3 Hz, 3 Hz, and 5 Hz, respectively.
  • Peak forces measured were 1.4 N, 2.9 N, and 3.0 N across the Cartesian coordinate system.
  • Observed workspace and orientation ranges were 50.1 × 39.8 × 58.2 mm³ and 40.4°/60.1°/63.1° for azimuth, elevation, and roll, respectively.

Conclusions:

  • The characterized mechanical parameters provide critical data for designing a compact, customized haptic hand-controller tailored to neurosurgical tasks.
  • This research facilitates the development of advanced haptic interfaces for realistic virtual neurosurgery training and execution within MRI environments.