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@article{Avery:2020:10.1109/tmrb.2020.3031636,
author = {Avery, J and Shulakova, D and Runciman, M and Mylonas, GP and Darzi, A},
doi = {10.1109/tmrb.2020.3031636},
journal = {IEEE Transactions on Medical Robotics and Bionics},
pages = {561--564},
title = {Tactile sensor for minimally invasive surgery using Electrical Impedance Tomography},
url = {http://dx.doi.org/10.1109/tmrb.2020.3031636},
volume = {2},
year = {2020}
}
TY - JOUR
AB - Whilst offering numerous benefits to patients, minimally invasive surgery (MIS) has a disadvantage in the loss of tactile feedback to the surgeon, traditionally offering valuable qualitative tissue assessment, such as tumour identification and localisation. Tactile sensors aim to overcome this loss of sensation by detecting tissue characteristics such as stiffness, composition and temperature. Tactile sensors have previously been incorporated into MIS robotic end effectors, which require lengthy scanning procedures due to localised sensitivity. Distributed tactile sensors, or “artificial skin” offer a map of tissue properties in a single instance but are often not suitable for MIS applications due to limited biocompatibility or large collapsed volumes. We propose a deployable, soft, tactile sensor with a deformable saline chamber and integrated Electrical Impedance Tomography (EIT) electrodes. During contact with tissue, the saline is displaced from the chamber and the lesion size and stiffness can be inferred from the resultant impedance changes. Through optimisation of the EIT measurement protocol and hardware the sensor was capable of localising the centre of mass of palpation targets within 1.5 mm in simulation and 2.3–4.6mm in phantom experiments. Reconstructed image metrics differentiated target objects from 8–30 mm.
AU - Avery,J
AU - Shulakova,D
AU - Runciman,M
AU - Mylonas,GP
AU - Darzi,A
DO - 10.1109/tmrb.2020.3031636
EP - 564
PY - 2020///
SN - 2576-3202
SP - 561
TI - Tactile sensor for minimally invasive surgery using Electrical Impedance Tomography
T2 - IEEE Transactions on Medical Robotics and Bionics
UR - http://dx.doi.org/10.1109/tmrb.2020.3031636
UR - http://hdl.handle.net/10044/1/84767
VL - 2
ER -
