PMID- 31265381
OWN - NLM
STAT- MEDLINE
DCOM- 20210624
LR  - 20210624
IS  - 1558-2531 (Electronic)
IS  - 0018-9294 (Print)
IS  - 0018-9294 (Linking)
VI  - 67
IP  - 4
DP  - 2020 Apr
TI  - Toward Safe Retinal Microsurgery: Development and Evaluation of an RNN-Based 
      Active Interventional Control Framework.
PG  - 966-977
LID - 10.1109/TBME.2019.2926060 [doi]
AB  - OBJECTIVE: Robotics-assisted retinal microsurgery provides several benefits 
      including improvement of manipulation precision. The assistance provided to the 
      surgeons by current robotic frameworks is, however, a "passive" support, e.g., by 
      damping hand tremor. Intelligent assistance and active guidance are, however, 
      lacking in the existing robotic frameworks. In this paper, an active 
      interventional control framework (AICF) has been presented to increase operation 
      safety by actively intervening the operation to avoid exertion of excessive 
      forces to the sclera. METHODS: AICF consists of the following four components: 
      first, the steady-hand eye robot as the robotic module; second, a sensorized tool 
      to measure tool-to-sclera forces; third, a recurrent neural network to predict 
      occurrence of undesired events based on a short history of time series of sensor 
      measurements; and finally, a variable admittance controller to command the robot 
      away from the undesired instances. RESULTS: A set of user studies were conducted 
      involving 14 participants (with four surgeons). The users were asked to perform a 
      vessel-following task on an eyeball phantom with the assistance of AICF as well 
      as other two benchmark approaches, i.e., auditory feedback (AF) and real-time 
      force feedback (RF). Statistical analysis shows that AICF results in a 
      significant reduction of proportion of undesired instances to about 2.5%, 
      compared with 38.4% and 26.2% using AF and RF, respectively. CONCLUSION: AICF can 
      effectively predict excessive-force instances and augment performance of the user 
      to avoid undesired events during robot-assisted microsurgical tasks. 
      SIGNIFICANCE: The proposed system may be extended to other fields of microsurgery 
      and may potentially reduce tissue injury.
FAU - He, Changyan
AU  - He C
FAU - Patel, Niravkumar
AU  - Patel N
FAU - Shahbazi, Mahya
AU  - Shahbazi M
FAU - Yang, Yang
AU  - Yang Y
FAU - Gehlbach, Peter
AU  - Gehlbach P
FAU - Kobilarov, Marin
AU  - Kobilarov M
FAU - Iordachita, Iulian
AU  - Iordachita I
LA  - eng
GR  - R01 EB023943/EB/NIBIB NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20190701
PL  - United States
TA  - IEEE Trans Biomed Eng
JT  - IEEE transactions on bio-medical engineering
JID - 0012737
SB  - IM
MH  - Humans
MH  - Microsurgery
MH  - Retina
MH  - *Robotic Surgical Procedures
MH  - *Robotics
MH  - Sclera
PMC - PMC7197394
MID - NIHMS1579036
EDAT- 2019/07/03 06:00
MHDA- 2021/06/25 06:00
PMCR- 2021/04/01
CRDT- 2019/07/03 06:00
PHST- 2019/07/03 06:00 [pubmed]
PHST- 2021/06/25 06:00 [medline]
PHST- 2019/07/03 06:00 [entrez]
PHST- 2021/04/01 00:00 [pmc-release]
AID - 10.1109/TBME.2019.2926060 [doi]
PST - ppublish
SO  - IEEE Trans Biomed Eng. 2020 Apr;67(4):966-977. doi: 10.1109/TBME.2019.2926060. 
      Epub 2019 Jul 1.