Prediction of Low Back Pain with Two Expert Systems

Authors:
Murat Sari;Eyyup Gulbandilar;Ali Cimbiz
Affiliations:
Department of Mathematics, Faculty of Art and Science, Pamukkale University, Denizli, Turkey 20070;Department of Computer Engineering, Faculty of Engineering, Dumlupinar University, Kutahya, Turkey 43100;Department of Physical Therapy and Rehabilitations, Health Institution, Dumlupinar University, Kutahya, Turkey 43100
Venue:
Journal of Medical Systems
Year:
2012

Citing 4
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Abstract

Low back pain (LBP) is one of the common problems encountered in medical applications. This paper proposes two expert systems (artificial neural network and adaptive neuro-fuzzy inference system) for the assessment of the LBP level objectively. The skin resistance and visual analog scale (VAS) values have been accepted as the input variables for the developed systems. The results showed that the expert systems behave very similar to real data and that use of the expert systems can be used to successfully diagnose the back pain intensity. The suggested systems were found to be advantageous approaches in addition to existing unbiased approaches. So far as the authors are aware, this is the first attempt of using the two expert systems achieving very good performance in a real application. In light of some of the limitations of this study, we also identify and discuss several areas that need continued investigation.