• Safak Sahir Karamehmetoglu, Mukden Ugur, Yunus Ziya Arslan, and Deniz Palamar.
• Physical Medicine and Rehabilitation Department, Cerrahpasa Medical Faculty, Istanbul University, Cerrahpasa, Istanbul, 34098, Turkey. karamehm@istanbul.edu.tr
• Eur Spine J. 2009 Jul 1; 18 (7): 972977972-7.

AbstractThe purpose of this study was to develop a quantitative skin impedance test that could be used to diagnose spinal cord injury (SCI) if any, especially in unconscious and/or non-cooperative SCI patients. To achieve this goal, initially skin impedance of the sensory key points of the dermatomes (between C3 and S1 bilaterally) was measured in 15 traumatic SCI patients (13 paraplegics and 2 tetraplegics) and 15 control subjects. In order to classify impedance values and to observe whether there would be a significant difference between patient and subject impedances, an artificial neural network (ANN) with back-propagation algorithm was employed. Validation results of the ANN showed promising performance. It could classify traumatic SCI patients with a success rate of 73%. By assessing the experimental protocols and the validation results, the proposed method seemed to be a simple, objective, quantitative, non-invasive and non-expensive way of assessing SCI in such patients.

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