TY - JOUR
T1 - Motorized microforceps with active motion guidance based on common-path SSOCT for epiretinal membranectomy
AU - Cheon, Gyeong Woo
AU - Gonenc, Berk
AU - Taylor, Russell H.
AU - Gehlbach, Peter L.
AU - Kang, Jin U.
N1 - Funding Information:
Manuscript received September 6, 2016; revised January 6, 2017, April 5, 2017, and July 11, 2017; accepted August 9, 2017. Date of publication September 4, 2017; date of current version December 13, 2017. Recommended by Technical Editor F. Janabi-Sharifi. This work was supported in part by the U.S. National Institute of Health and the National Eye Institute under Grant R01EY021540-01, and in part by Research to Prevent Blindness, New York, NY, USA. (Corresponding author: Gyeong Woo Cheon.) G. W. Cheon and J. U. Kang are with the Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218 USA (e-mail: gcheon1@jhu.edu; jkang@jhu.edu).
Publisher Copyright:
© 1996-2012 IEEE.
PY - 2017/12
Y1 - 2017/12
N2 - In this study, we built and tested a handheld motion-guided microforceps system using common-path swept source optical coherence tomography (CP-SSOCT) for highly accurate depth controlled epiretinal membranectomy. A touch sensor and two motors were used in the forceps design to minimize the inherent motion artifact while squeezing the tool handle to actuate the tool and grasp, and to independently control the depth of the tool-tip. A smart motion monitoring and a guiding algorithm were devised to provide precise and intuitive freehand control. We compared the involuntary tool-tip motion occurring while grasping with a standard manual microforceps and our touch sensor activated microforceps. The results showed that our touch-sensor-based and motor-actuated tool can significantly attenuate the motion artifact during grasping (119.81 μm with our device versus 330.73 μm with the standard microforceps). By activating the CP-SSOCT-based depth locking feature, the erroneous tool-tip motion can be further reduced down to 5.11 μm. We evaluated the performance of our device in comparison with the standard instrument in terms of the elapsed time, the number of grasping attempts, and the maximum depth of damage created on the substrate surface while trying to pick up small pieces of fibers (O 125 μm) from a soft polymer surface. The results indicate that all metrics were significantly improved when using our device, of note, the average elapsed time, the number of grasping attempts, and the maximum depth of damage were reduced by 25%, 31%, and 75%, respectively.
AB - In this study, we built and tested a handheld motion-guided microforceps system using common-path swept source optical coherence tomography (CP-SSOCT) for highly accurate depth controlled epiretinal membranectomy. A touch sensor and two motors were used in the forceps design to minimize the inherent motion artifact while squeezing the tool handle to actuate the tool and grasp, and to independently control the depth of the tool-tip. A smart motion monitoring and a guiding algorithm were devised to provide precise and intuitive freehand control. We compared the involuntary tool-tip motion occurring while grasping with a standard manual microforceps and our touch sensor activated microforceps. The results showed that our touch-sensor-based and motor-actuated tool can significantly attenuate the motion artifact during grasping (119.81 μm with our device versus 330.73 μm with the standard microforceps). By activating the CP-SSOCT-based depth locking feature, the erroneous tool-tip motion can be further reduced down to 5.11 μm. We evaluated the performance of our device in comparison with the standard instrument in terms of the elapsed time, the number of grasping attempts, and the maximum depth of damage created on the substrate surface while trying to pick up small pieces of fibers (O 125 μm) from a soft polymer surface. The results indicate that all metrics were significantly improved when using our device, of note, the average elapsed time, the number of grasping attempts, and the maximum depth of damage were reduced by 25%, 31%, and 75%, respectively.
KW - Biomedical optical imaging
KW - Image sensors
KW - Optical signal detection
KW - Optical signal processing
KW - Surgery
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U2 - 10.1109/TMECH.2017.2749384
DO - 10.1109/TMECH.2017.2749384
M3 - Article
C2 - 29628753
AN - SCOPUS:85029183636
SN - 1083-4435
VL - 22
SP - 2440
EP - 2448
JO - IEEE/ASME Transactions on Mechatronics
JF - IEEE/ASME Transactions on Mechatronics
IS - 6
M1 - 8025820
ER -