Direct Bladder Contraction by Single and Multi-Electrode Stimulation

Yifan Wang, Philippe Zimmern, Mario I. Romero-Ortega

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Detrusor sphincter dyssynergia (DSD) is characterized by the uncoordinated activity between contraction of the detrusor and relaxation of the external urinary sphincter, affecting 70%-84% of individuals with spinal cord injury (SCI). Current treatments include catheterization, medication, sphincterotomy, and neuromodulation. Here we divided the bladder in quarters and used point (0.78 mm2) electrical stimulation at 0.5, 1.0 and 2 mA to map those that evoked maximal contraction (9.88 mm2), as determined by vascular fiduciary markers before and after stimulation. A multi-electrode array was then used to reduce the electrodes size (2000μm2) which evoked a more efficient bladder contraction (16.51 mm2) and at a lower threshold (0.15 mA). The relative change of bladder size evoked by single electrodes was -7.3 %, whereas that evoked by the multichannel electrode was 12.9% (p = 0.007). This result defines the optimal targets sites and parameters that can be used to improve the neuromodulation treatment of DSD.

Original languageEnglish (US)
Title of host publication11th International IEEE/EMBS Conference on Neural Engineering, NER 2023 - Proceedings
PublisherIEEE Computer Society
ISBN (Electronic)9781665462921
DOIs
StatePublished - 2023
Event11th International IEEE/EMBS Conference on Neural Engineering, NER 2023 - Baltimore, United States
Duration: Apr 25 2023Apr 27 2023

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2023-April
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Conference

Conference11th International IEEE/EMBS Conference on Neural Engineering, NER 2023
Country/TerritoryUnited States
CityBaltimore
Period4/25/234/27/23

Keywords

  • DSD
  • SCI
  • bladder mapping
  • direct bladder stimulation
  • multi-electrode stimulation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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