Selective Recording of Urinary Bladder Fullness from the Extradural Sacral Roots

B. Metcalfe, N. Granger, J. Prager, S. Sadrafshari, T. Grego, J. Taylor, N. Donaldson

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

2 Citations (SciVal)
20 Downloads (Pure)

Abstract

Managing the urinary bladder is of primary importance to clinicians and patients after trauma to the spinal cord. Sacral Anterior Root Stimulators that control the bladder have been available as clinical technology for many years, however these devices cannot measure the fullness of the urinary bladder or detect the onset of reflex voiding. In order to address this fundamental limitation, it is necessary to develop a method for recording the neural signals that encode bladder fullness. This paper presents a proof of concept technique for recording bladder afferents from the extradural sacral roots using a multiple electrode cuff. Results are provided from acute in-vivo experiments performed in sheep.

Original languageEnglish
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherIEEE
Pages3873-3876
Number of pages4
ISBN (Electronic)9781728119908
DOIs
Publication statusPublished - 27 Aug 2020
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: 20 Jul 202024 Jul 2020

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Country/TerritoryCanada
CityMontreal
Period20/07/2024/07/20

ASJC Scopus subject areas

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

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