“…Nevertheless, for our other aims - including quantitative assessment of differing surgical techniques, objective evaluation of the surgical performance and accurate modeling of retinal tissues – our future work aims to further improve the axial sensing accuracy. Some potential methods include using higher order nonlinear models for force computation, and exploring customized sensor architectures that provide better decoupling between axial and transverse forces [62]. …”
In vitreoretinal surgery, membrane peeling is a prototypical task where a layer of fibrous tissue is delaminated off the retina with a micro-forceps by applying very fine forces that are mostly imperceptible to the surgeon. Previously we developed sensitized ophthalmic surgery tools based on fiber Bragg grating (FBG) strain sensors, which were shown to precisely detect forces at the instrument’s tip in two degrees of freedom perpendicular to the tool axis. This paper presents a new design that employs an additional sensor to capture also the tensile force along the tool axis. The grasping functionality is provided via a compact motorized unit. To compute forces, we investigate two distinct fitting methods: a linear regression and a nonlinear fitting based on second-order Bernstein polynomials. We carry out experiments to test the repeatability of sensor outputs, calibrate the sensor and validate its performance. Results demonstrate sensor wavelength repeatability within 2 pm. Although the linear method provides sufficient accuracy in measuring transverse forces, in the axial direction it produces a root mean square (rms) error over 3 mN even for a confined magnitude and direction of forces. On the other hand, the nonlinear method provides a more consistent and accurate measurement of both the transverse and axial forces for the entire force range (0–25 mN). Validation including random samples shows that our tool with the nonlinear force computation method can predict 3-D forces with an rms error under 0.15 mN in the transverse plane and within 2 mN accuracy in the axial direction.
“…Nevertheless, for our other aims - including quantitative assessment of differing surgical techniques, objective evaluation of the surgical performance and accurate modeling of retinal tissues – our future work aims to further improve the axial sensing accuracy. Some potential methods include using higher order nonlinear models for force computation, and exploring customized sensor architectures that provide better decoupling between axial and transverse forces [62]. …”
In vitreoretinal surgery, membrane peeling is a prototypical task where a layer of fibrous tissue is delaminated off the retina with a micro-forceps by applying very fine forces that are mostly imperceptible to the surgeon. Previously we developed sensitized ophthalmic surgery tools based on fiber Bragg grating (FBG) strain sensors, which were shown to precisely detect forces at the instrument’s tip in two degrees of freedom perpendicular to the tool axis. This paper presents a new design that employs an additional sensor to capture also the tensile force along the tool axis. The grasping functionality is provided via a compact motorized unit. To compute forces, we investigate two distinct fitting methods: a linear regression and a nonlinear fitting based on second-order Bernstein polynomials. We carry out experiments to test the repeatability of sensor outputs, calibrate the sensor and validate its performance. Results demonstrate sensor wavelength repeatability within 2 pm. Although the linear method provides sufficient accuracy in measuring transverse forces, in the axial direction it produces a root mean square (rms) error over 3 mN even for a confined magnitude and direction of forces. On the other hand, the nonlinear method provides a more consistent and accurate measurement of both the transverse and axial forces for the entire force range (0–25 mN). Validation including random samples shows that our tool with the nonlinear force computation method can predict 3-D forces with an rms error under 0.15 mN in the transverse plane and within 2 mN accuracy in the axial direction.
“…They relied on mechanical means to mitigate the effect of the crosssensitivity of the WSIM. Our previous work in [12]- [14] have demonstrated theoretically that, the cross-talk noise caused by the simultaneous two forces can be decoupled completely. Our method is mainly combined both Bandwidth modulation method (BMM) and customized FBGs including TFBG technique.…”
Section: An Additional Advantage Of Tfbg Is Its Tiny Cross-sectionalmentioning
“…sensor allows it to perform independently from the power fluctuations of the laser source [2], [3]. The vast applications of FBG sensor has made it an attractive sensing solution ranging from the field of civil engineering to the biomedical application [4]- [7]. Even though FBG sensor is a type of point sensor, multiplexing capability of FBG has made quasidistribution measurement scheme available.…”
We report on the experimental results of the combination of unique auto-correlation properties of Golay complementary code and Hadamard matrix properties of standard simplex code. The combination of the two coding techniques results in improvement of the signal-to-noise ratio (SNR) of time domain multiplexed fiber Bragg grating (TDM-FBG) sensor for temperature measurement. Previously, we have analyzed the properties of both coding techniques when deployed separately in the TDM-FBG sensor. In this case, both coding techniques result in the same amount of SNR improvement for code length longer than 31 bits. In this paper, we demonstrate the combination and simultaneous deployment of the two techniques to measure multiple FBGs under room condition (25 • C) and 50 • C temperature. The two schemes combination results in remarkable improvement of SNR and still retains the original spatial property of the decoded FBG signals, confirming the successful deployment of the hybrid codes. From the measurement of two FBG sensors located after 16 km of fiber, the combination of 31 bits of simplex-and 64 bits of Golay codes has resulted in a total of 10.5 dB improvement of SNR.
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