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A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle
In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698970/ https://www.ncbi.nlm.nih.gov/pubmed/33218118 http://dx.doi.org/10.3390/s20226607 |
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author | Zhang, Yingxuan Ju, Feng Wei, Xiaoyong Wang, Dan Wang, Yaoyao |
author_facet | Zhang, Yingxuan Ju, Feng Wei, Xiaoyong Wang, Dan Wang, Yaoyao |
author_sort | Zhang, Yingxuan |
collection | PubMed |
description | In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direction. It solves the problem that existing sensors can only detect in the normal direction to ensure accuracy when the degree of freedom (DOF) of surgical instruments is limited. The proposed senor can distinguish samples with different stiffness and recognize lump from normal tissue effectively when the contact angle varies within [0°, 45°]. These are achieved by establishing a new detection model and sensor optimization. It deduces the influence of contact angle on stiffness detection by sensor parameters design and optimization. The detection performance of the sensor is confirmed by simulation and experiment. Five samples with different stiffness (including lump and normal samples with close stiffness) are used. Through blind recognition test in simulation, the recognition rate is 100% when the contact angle is randomly selected within 30°, 94.1% within 45°, which is 38.7% higher than the unoptimized sensor. Through blind classification test and automatic k-means clustering in experiment, the correct rate is 92% when the contact angle is randomly selected within 45°. We can get the proposed sensor can easily recognize samples with different stiffness with high accuracy which has broad application prospects in the medical field. |
format | Online Article Text |
id | pubmed-7698970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76989702020-11-29 A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle Zhang, Yingxuan Ju, Feng Wei, Xiaoyong Wang, Dan Wang, Yaoyao Sensors (Basel) Article In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direction. It solves the problem that existing sensors can only detect in the normal direction to ensure accuracy when the degree of freedom (DOF) of surgical instruments is limited. The proposed senor can distinguish samples with different stiffness and recognize lump from normal tissue effectively when the contact angle varies within [0°, 45°]. These are achieved by establishing a new detection model and sensor optimization. It deduces the influence of contact angle on stiffness detection by sensor parameters design and optimization. The detection performance of the sensor is confirmed by simulation and experiment. Five samples with different stiffness (including lump and normal samples with close stiffness) are used. Through blind recognition test in simulation, the recognition rate is 100% when the contact angle is randomly selected within 30°, 94.1% within 45°, which is 38.7% higher than the unoptimized sensor. Through blind classification test and automatic k-means clustering in experiment, the correct rate is 92% when the contact angle is randomly selected within 45°. We can get the proposed sensor can easily recognize samples with different stiffness with high accuracy which has broad application prospects in the medical field. MDPI 2020-11-18 /pmc/articles/PMC7698970/ /pubmed/33218118 http://dx.doi.org/10.3390/s20226607 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Yingxuan Ju, Feng Wei, Xiaoyong Wang, Dan Wang, Yaoyao A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle |
title | A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle |
title_full | A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle |
title_fullStr | A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle |
title_full_unstemmed | A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle |
title_short | A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle |
title_sort | piezoelectric tactile sensor for tissue stiffness detection with arbitrary contact angle |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698970/ https://www.ncbi.nlm.nih.gov/pubmed/33218118 http://dx.doi.org/10.3390/s20226607 |
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