Transvascular Electrode Model and Stimulation Parameters Estimation

Authors

  • Jessica Kit-Sum Tang Simon Fraser University Lungpacer Medical,Inc.
  • Joaquin Andres Hoffer Simon Fraser University Lungpacer Medical Inc.

Abstract

For patients who require mechanical ventilation, phrenic nerve pacing or diaphragm muscle  pacing are alternative methods that can provide a more natural form of breathing. However,  existing electrode implantation methods require lengthy surgery under full anaesthesia, for  which many patients are ineligible. We are developing an alternative, transvascular phrenic  nerve stimulation method that requires a much less invasive implant method, reduces the  physical demands on the patient and can be used for periods of days or weeks, such as is  required for intensive care patients on mechanical ventilation. Specialized intravascular  electrodes are inserted and deployed inside a central vein in close proximity to the target  phrenic nerves. To help guide the design of intravascular electrodes, we have modeled the  dielectric properties of the vessel wall, surrounding tissues and fluid and determined how these  parameters alter the dispersion of the electric field and influence stimulation efficacy for  various electrode geometries and locations. Stimulation selectivity of the phrenic nerves is  highly dependent on electrode proximity and is substantially enhanced by the addition of an  insulating electrode backing in our model. We will describe stimulation parameters and  guidelines that helped us predict the recruitment level and selectivity that can be obtained with  intravascular phrenic nerve stimulation in an animal model.

Author Biographies

Jessica Kit-Sum Tang, Simon Fraser University Lungpacer Medical,Inc.

School of Engineering Science

Joaquin Andres Hoffer, Simon Fraser University Lungpacer Medical Inc.

Department of Biomedical Physiology and Kinesiology

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Published

2010-06-15

How to Cite

[1]
J. K.-S. Tang and J. A. Hoffer, “Transvascular Electrode Model and Stimulation Parameters Estimation”, CMBES Proc., vol. 33, no. 1, Jun. 2010.

Issue

Section

Academic