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Prediction of Low Back Pain with Two Expert Systems

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.

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Acknowledgement

For their generous contribution to the conducted study, the employees at the Dumlupinar University, Medical Faculty, Department of Physical Therapy and Rehabilitation outpatient clinic are appreciated.

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Correspondence to Eyyup Gulbandilar.

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Sari, M., Gulbandilar, E. & Cimbiz, A. Prediction of Low Back Pain with Two Expert Systems. J Med Syst 36, 1523–1527 (2012). https://doi.org/10.1007/s10916-010-9613-x

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Keywords

  • Low back pain
  • Artificial neural network (ANN)
  • Adaptive neuro-fuzzy inference system (ANFIS)
  • Modeling
  • Skin resistance
  • Expert system
  • Visual analog scale