Now showing items 1-2 of 2

    • Image-based classification of bladder state using electrical impedance tomography 

      Dunne, Eoghan; Santorelli, Adam; McGinley, Brian; Leader, Geraldine; O'Halloran, Martin; Porter, Emily (IOP Publishing, 2018-12-03)
      Objective: In this study, we examine the potential of using machine learning classification to determine the bladder state ( not full , full ) with electrical impedance tomography (EIT) images of the pelvic region. Accurate ...
    • Supervised learning classifiers for electrical impedance-based bladder state detection 

      Dunne, Eoghan; Santorelli, Adam; McGinley, Brian; Leader, Geraldine; O’Halloran, Martin; Porter, Emily (Nature Publishing Group, 2018-03-29)
      Urinary Incontinence affects over 200 million people worldwide, severely impacting the quality of life of individuals. Bladder state detection technology has the potential to improve the lives of people with urinary ...