3-DOF Force-Sensing Motorized Micro-Forceps for Robot-Assisted Vitreoretinal Surgery

3-DOF Force-Sensing Motorized Micro-Forceps for Robot-Assisted Vitreoretinal Surgery. Gonenc, B., Chamani, A., Handa, J., Gehlbach, P., Taylor, R. H., & Iordachita, I. IEEE Sensors Journal, 17(11):3526–3541, June, 2017.

Paper doi abstract bibtex

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 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.

@article{gonenc_3-dof_2017,
	title = {3-{DOF} {Force}-{Sensing} {Motorized} {Micro}-{Forceps} for {Robot}-{Assisted} {Vitreoretinal} {Surgery}},
	volume = {17},
	issn = {1530-437X, 1558-1748, 2379-9153},
	url = {http://ieeexplore.ieee.org/document/7903591/},
	doi = {10.1109/JSEN.2017.2694965},
	abstract = {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 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.},
	language = {en},
	number = {11},
	urldate = {2020-04-21},
	journal = {IEEE Sensors Journal},
	author = {Gonenc, Berk and Chamani, Alireza and Handa, James and Gehlbach, Peter and Taylor, Russell H. and Iordachita, Iulian},
	month = jun,
	year = {2017},
	pages = {3526--3541},
}

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