Learning-based Parameter Estimation for Hysteresis Modeling in Robotic Catheterization

Olatunji Mumini Omisore, Shipeng Han, Tao Zhou, Yousef Al-Handarish, Wenjing Du, Kamen Ivanov, Lei Wang

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In the last half decade, nearly 31% of annual global deaths are linked to cardiovascular diseases. Thus, robotic catheterizations are recently proposed for interventions of conditions such as aneurism or atherosclerosis formed along vascular paths leading to the heart. However, existence of mild to strong hysteresis while navigating unactuated catheters with the current robotic systems inhibits autonomous control for vascular surgery. Thus, immersion of surgeons remains high with most of their time spent on steering the catheter in-and-out of the vessels. In this study, an autoregressive nonlinear neural network model is adapted for parameterization of vital causal factors of hysteresis during robotic catheterization. Crucial for autonomous control, hysteretic behaviors of endovascular tool are modeled while suitable values are estimated and analyzed for five contributory factors. The network model is validated with hysteresis data we obtained from a two degree-of-freedom robotic system and an unactuated catheter. Result validation shows accurate description of the hysteresis profile recorded duirng catheterization trials with a vascular phantom model.

Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5399-5402
Number of pages4
ISBN (Electronic)9781538613115
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
Duration: 23 Jul 201927 Jul 2019

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Country/TerritoryGermany
CityBerlin
Period23/07/1927/07/19

Keywords

  • Autonomous Control
  • Hysteresis Modeling
  • Neural Network
  • Parameter Estimation
  • Robotic Catheterization

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint

Dive into the research topics of 'Learning-based Parameter Estimation for Hysteresis Modeling in Robotic Catheterization'. Together they form a unique fingerprint.

Cite this