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MRI-VisAct: a Bowden-cable-driven MRI-compatible series viscoelastic actuator.

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Title: MRI-VisAct: a Bowden-cable-driven MRI-compatible series viscoelastic actuator.
Authors: Senturk, Yusuf Mert1, Patoglu, Volkan1 vpatoglu@sabanciuniv.edu
Source: Transactions of the Institute of Measurement & Control. May2018, Vol. 40 Issue 8, p2440-2453. 14p.
Subjects: Magnetic resonance imaging, Robotics, Human-robot interaction, Human-computer interaction, Robots
Abstract: The presence of strong magnetic fields in the magnetic resonance imaging (MRI) environment limits the integration of robotic rehabilitation systems in the MRI process. The tendency to improve imaging quality by the amplification of magnetic field strength further tightens the bidirectional compatibility constraints on MRI-compatible rehabilitation devices. We present the design, control and characterization of MRI-VisAct-- a low-cost, Bowden-cableactuated rotary series viscoelastic actuator that satisfies the bidirectional compatibility requirements to the maximum extent. Components of MRIVisAct that are placed in the magnet room are built using nonconductive, diamagnetic MRI-compatible materials, while ferromagnetic or paramagnetic components are placed in the control room, located outside the MRI room. Power and data transmission are achieved through Bowden cables and fibre optics, respectively. This arrangement ensures that neuroimaging artefacts are minimized, while eliminating safety hazards, and device performance is not affected by the magnetic field. MRI-VisAct works under closed-loop torque control enabled through series viscoelastic actuation. MRI-VisAct is fully customizable; it can serve as a building block of higher-degrees-of-freedom MRI-compatible robotic devices. [ABSTRACT FROM AUTHOR]
Copyright of Transactions of the Institute of Measurement & Control is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: The presence of strong magnetic fields in the magnetic resonance imaging (MRI) environment limits the integration of robotic rehabilitation systems in the MRI process. The tendency to improve imaging quality by the amplification of magnetic field strength further tightens the bidirectional compatibility constraints on MRI-compatible rehabilitation devices. We present the design, control and characterization of MRI-VisAct-- a low-cost, Bowden-cableactuated rotary series viscoelastic actuator that satisfies the bidirectional compatibility requirements to the maximum extent. Components of MRIVisAct that are placed in the magnet room are built using nonconductive, diamagnetic MRI-compatible materials, while ferromagnetic or paramagnetic components are placed in the control room, located outside the MRI room. Power and data transmission are achieved through Bowden cables and fibre optics, respectively. This arrangement ensures that neuroimaging artefacts are minimized, while eliminating safety hazards, and device performance is not affected by the magnetic field. MRI-VisAct works under closed-loop torque control enabled through series viscoelastic actuation. MRI-VisAct is fully customizable; it can serve as a building block of higher-degrees-of-freedom MRI-compatible robotic devices. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Transactions of the Institute of Measurement & Control is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Type: general
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              Text: May2018
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