Multi-frequency symmetry difference electrical impedance tomography with machine learning for human stroke diagnosis.

Journal: Physiological measurement
Published Date:

Abstract

OBJECTIVE: Multi-frequency symmetry difference electrical impedance tomography (MFSD-EIT) can robustly detect and identify unilateral perturbations in symmetric scenes. Here, an investigation is performed to assess if the algorithm can be successfully applied to identify the aetiology of stroke with the aid of machine learning.

Authors

  • Barry McDermott
    Translational Medical Device Lab, National University of Ireland, Galway, Ireland.
  • Adnan Elahi
  • Adam Santorelli
    School of Nursing and Midwifery, NUI Galway Ireland.
  • Martin O'Halloran
    Translational Medical Device Lab (tmdlab.ie), National University of Ireland Galway, Galway, Ireland.
  • James Avery
  • Emily Porter
    Translational Medical Device Lab (tmdlab.ie), National University of Ireland Galway, Galway, Ireland.