Adaptation of a Haptic Robot in a 3T fMRI
Identifieur interne : 001483 ( Pmc/Curation ); précédent : 001482; suivant : 001484Adaptation of a Haptic Robot in a 3T fMRI
Auteurs : Joseph Snider ; Markus Plank ; Larry May ; Thomas T. Liu ; Howard PoiznerSource :
- Journal of Visualized Experiments : JoVE [ 1940-087X ] ; 2011.
Abstract
Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal 1 with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data 2, and nearly real-time analyses 3. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot 4 allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1).
The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments 5, 6, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ˜380 to ˜330, and ˜250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (˜2.6 lbs) but extremely stiff 3/4" graphite and well balanced on the 3DoF joint in the middle. The end result is an fMRI compatible, haptic system with about 1 cubic foot of working space, and, when combined with virtual reality, it allows for a new set of experiments to be performed in the fMRI environment including naturalistic reaching, passive displacement of the limb and haptic perception, adaptation learning in varying force fields, or texture identification 5, 6.
Url:
DOI: 10.3791/3364
PubMed: 21989084
PubMed Central: 3227168
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Joseph Snider<affiliation><nlm:aff id="I591D3104">Institute for Neural Computation, University of California</nlm:aff>
<wicri:noCountry code="subfield">University of California</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="I591D3104">Institute for Neural Computation, University of California</nlm:aff>
<wicri:noCountry code="subfield">University of California</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="I591D2901">Department of Radiology, University of California</nlm:aff>
<wicri:noCountry code="subfield">University of California</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="I591D2901">Department of Radiology, University of California</nlm:aff>
<wicri:noCountry code="subfield">University of California</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="I591D3105">Department of Cognitive Science and Program in Neurosciences, University of California</nlm:aff>
<wicri:noCountry code="subfield">University of California</wicri:noCountry>
</affiliation>
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<front><div type="abstract" xml:lang="en"><p>Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal <sup>1</sup>
with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data <sup>2</sup>
, and nearly real-time analyses <sup>3</sup>
. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot <sup>4</sup>
allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1).</p>
<p>The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments <sup>5, 6</sup>
, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ˜380 to ˜330, and ˜250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (˜2.6 lbs) but extremely stiff 3/4" graphite and well balanced on the 3DoF joint in the middle. The end result is an fMRI compatible, haptic system with about 1 cubic foot of working space, and, when combined with virtual reality, it allows for a new set of experiments to be performed in the fMRI environment including naturalistic reaching, passive displacement of the limb and haptic perception, adaptation learning in varying force fields, or texture identification <sup>5, 6</sup>
.</p>
</div>
</front>
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<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Vis Exp</journal-id>
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<article-categories><subj-group subj-group-type="heading"><subject>Bioengineering</subject>
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<title-group><article-title>Adaptation of a Haptic Robot in a 3T fMRI</article-title>
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<contrib-group><contrib contrib-type="author"><name><surname>Snider</surname>
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<aff id="I591D3104">Institute for Neural Computation, University of California</aff>
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<aff id="I591D3105">Department of Cognitive Science and Program in Neurosciences, University of California</aff>
<author-notes><fn><p>Correspondence to: Howard Poizner at <email>hpoizner@ucsd.edu</email>
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<pub-date pub-type="collection"><year>2011</year>
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<pub-date pub-type="epub"><day>4</day>
<month>10</month>
<year>2011</year>
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<issue>56</issue>
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<permissions><copyright-statement>Copyright © 2011, Journal of Visualized Experiments</copyright-statement>
<copyright-year>2011</copyright-year>
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<abstract><p>Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal <sup>1</sup>
with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data <sup>2</sup>
, and nearly real-time analyses <sup>3</sup>
. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot <sup>4</sup>
allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1).</p>
<p>The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments <sup>5, 6</sup>
, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ˜380 to ˜330, and ˜250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (˜2.6 lbs) but extremely stiff 3/4" graphite and well balanced on the 3DoF joint in the middle. The end result is an fMRI compatible, haptic system with about 1 cubic foot of working space, and, when combined with virtual reality, it allows for a new set of experiments to be performed in the fMRI environment including naturalistic reaching, passive displacement of the limb and haptic perception, adaptation learning in varying force fields, or texture identification <sup>5, 6</sup>
.</p>
</abstract>
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