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Abelardo Escoto

dblp:69/8370 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 1 first-authorSystems, architecture and hardware · 3 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Medical and health informatics · 100%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics › surgical robotics
minimally invasive surgery
0.322015
A multi-sensory mechatronic device for localizing tumors in minimally invasive interventions · ICRA 2015
Force/position-based modular system for minimally invasive surgery · ICRA 2010
Medical and health informatics › computational pathology
tumor localization
0.212015
A multi-sensory mechatronic device for localizing tumors in minimally invasive interventions · ICRA 2015
Medical and health informatics
computer-assisted surgery
0.112010
Force/position-based modular system for minimally invasive surgery · ICRA 2010
Medical and health informatics
surgical robotics
0.112010
Force/position-based modular system for minimally invasive surgery · ICRA 2010
Robotics › Robot manipulation
tactile sensing
0.112015
A multi-sensory mechatronic device for localizing tumors in minimally invasive interventions · ICRA 2015

Methods — techniques the papers use, named apart from their topics

ultrasound sensing · 0.4fluoroscopic imaging · 0.4image-based position tracking · 0.1
YearPublicationVenuePosition
2017 Development of an optical fiber-based sensor for grasping and axial force sensing
abstract
In spite of the remarkable benefits that minimally invasive surgery provides for patients, the absence of force feedback is still a significant disadvantage. Several studies have been performed to address this issue; however, an accurate sterilizable force sensing technology for measuring axial and grasping forces is still missing. In this work, an innovative partial grasper has been designed and developed for a laparoscopic needle driver that can measure axial and grasping force information at the grasper tip. Fiber Bragg Grating sensors are used in this work because of their sterilizability and high sensitivity. Accuracies of 0.19 N and 0.26 N were achieved for the grasping and axial sensors respectively.
Pouya Soltani Zarrin, Abelardo Escoto, Ran Xu 0010, Rajnikant V. Patel, Michael D. Naish, Ana Luisa Trejos
ICRA2
2015 A multi-sensory mechatronic device for localizing tumors in minimally invasive interventions
abstract
Tumor localization in traditional lung resection surgery requires manual palpation of the deflated lung through a thoracotomy. It is a painful procedure that is not suitable for many patients. Therefore, a multisensory mechatronic device was designed to localize tumors using a minimally invasive approach. The device is sensorized with tactile, ultrasound and position sensors in order to obtain multimodal data of soft tissue in real time. This paper presents the validation of the efficiency and efficacy of this device via an ex vivo experimental study. Tumor pathology was simulated by embedding iodine-agar phantom tumors of varying shapes and sizes into porcine liver tissue. The device was then used to palpate the tissue to localize and visualize the simulated tumors. Markers were then placed on the location of the tumors and fluoroscopic imaging was performed on the tissue in order to determine the localization accuracy of the device. Our results show that the device localized 87.5% of the tumors with an average deviation from the tumor center of 3.42 mm.
Abelardo Escoto, Srikanth Bhattad, Arefin Shamsil, Andre Sanches, Ana Luisa Trejos, Michael D. Naish, Richard Malthaner, Rajnikant V. Patel
ICRA1
2010 Force/position-based modular system for minimally invasive surgery
abstract
The limitations of minimally invasive surgery include the inability to sense forces exerted by the instruments on tissue and the limited visual cues available through the endoscope. A modular laparoscopic instrument capable of measuring force and position has been designed to address these limitations. Novel image-based position tracking software has been developed and integrated within a graphical user interface. This modular system is low cost, versatile, and could be used for training, localization of critical features or for guidance during surgical procedures.
Ana Luisa Trejos, Andrew C. Lyle, Abelardo Escoto, Michael D. Naish, Rajnikant V. Patel
ICRA3