| Literature DB >> 28652857 |
Hao Su1, Iulian I Iordachita2, Junichi Tokuda3, Nobuhiko Hata3, Xuan Liu4, Reza Seifabadi5, Sheng Xu5, Bradford Wood5, Gregory S Fischer6.
Abstract
Magnetic Resonance Imaging (MRI) provides both anatomical imaging with excellent soft tissue contrast and functional MRI imaging (fMRI) of physiological parameters. The last two decades have witnessed the manifestation of increased interest in MRI-guided minimally invasive intervention procedures and fMRI for rehabilitation and neuroscience research. Accompanying the aspiration to utilize MRI to provide imaging feedback during interventions and brain activity for neuroscience study, there is an accumulated effort to utilize force sensors compatible with the MRI environment to meet the growing demand of these procedures, with the goal of enhanced interventional safety and accuracy, improved efficacy and rehabilitation outcome. This paper summarizes the fundamental principles, the state of the art development and challenges of fiber optic force sensors for MRI-guided interventions and rehabilitation. It provides an overview of MRI-compatible fiber optic force sensors based on different sensing principles, including light intensity modulation, wavelength modulation, and phase modulation. Extensive design prototypes are reviewed to illustrate the detailed implementation of these principles. Advantages and disadvantages of the sensor designs are compared and analyzed. A perspective on the future development of fiber optic sensors is also presented which may have additional broad clinical applications. Future surgical interventions or rehabilitation will rely on intelligent force sensors to provide situational awareness to augment or complement human perception in these procedures.Entities:
Keywords: Fabry-Perot interferometer (FPI); Fiber optic sensor; MRI compatible robot; fiber Bragg grating (FBG); haptics; image-guided interventions; neuroscience; percutaneous interventions; rehabilitation
Year: 2017 PMID: 28652857 PMCID: PMC5482288 DOI: 10.1109/JSEN.2017.2654489
Source DB: PubMed Journal: IEEE Sens J ISSN: 1530-437X Impact factor: 3.301