An Abdominal phantom with tunable stiffness nodules and force sensing capability for palpation training
File(s)TRO_Liang_final.pdf (4.95 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
Robotic phantoms enable advanced physical examination training before using human patients. In this article, we present an abdominal phantom for palpation training with controllable stiffness liver nodules that can also sense palpation forces. The coupled sensing and actuation approach is achieved by pneumatic control of positive-granular jammed nodules for tunable stiffness. Soft sensing is done using the variation of internal pressure of the nodules under external forces. This article makes original contributions to extend the linear region of the neo-Hookean characteristic of the mechanical behavior of the nodules by 140% compared to no-jamming conditions and to propose a method using the organ level controllable nodules as sensors to estimate palpation position and force with a root-mean-square error of 4% and 6.5%, respectively. Compared to conventional soft sensors, the method allows the phantom to sense with no interference to the simulated physiological conditions when providing quantified feedback to trainees, and to enable training following current bare-hand examination protocols without the need to wear data gloves to collect data.
Date Issued
2021-08-01
Date Acceptance
2020-11-24
Citation
IEEE Transactions on Robotics, 2021, 37 (4), pp.1051-1064
ISSN
1552-3098
Publisher
Institute of Electrical and Electronics Engineers
Start Page
1051
End Page
1064
Journal / Book Title
IEEE Transactions on Robotics
Volume
37
Issue
4
Copyright Statement
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://ieeexplore.ieee.org/document/9310688
Grant Number
EP/R511547/1
EP/N03211X/2
EP/T00603X/1
Subjects
Industrial Engineering & Automation
0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
0913 Mechanical Engineering
Publication Status
Published
Date Publish Online
2020-12-29