Using fuzzy logic for diagnosis and classification of spasticity


Alcan V., Canal M. R., ZİNNUROĞLU M.

TURKISH JOURNAL OF MEDICAL SCIENCES, vol.47, no.1, pp.148-160, 2017 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 47 Issue: 1
  • Publication Date: 2017
  • Doi Number: 10.3906/sag-1512-65
  • Journal Name: TURKISH JOURNAL OF MEDICAL SCIENCES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.148-160
  • Keywords: Spasticity, surface electromyography, fuzzy logic, wavelet transform, PASSIVE STRETCH, ASHWORTH SCALES, EMG SIGNALS, H-REFLEX, STROKE, KNEE, HYPERTONIA, QUANTIFICATION, POSTSTROKE, WAVELET
  • Gazi University Affiliated: Yes

Abstract

Background/aim: Spasticity is generally defined as a sensory-motor control disorder. However, there is no pathophysiological mechanism or appropriate measurement and evaluation standards that can explain all aspects of a possible spasticity occurrence. The objective of this study is to develop a fuzzy logic classifier (FLC) diagnosis system, in which a quantitative evaluation is performed by surface electromyography (EMG), and investigate underlying pathophysiological mechanisms of spasticity.