Haptic rehabilitation exercises performance evaluation using automated inference systems

Ahmad Barghout, Atif Alamri, Mohamad Eid, Abdulmotaleb El Saddik

Research output: Contribution to journalArticlepeer-review


Haptics and virtual environments offer the opportunity to improve the traditional methods of stroke rehabilitation. Traditionally, a therapist has to subjectively evaluate the patient's performance. This paper aims to introduce an automated inference system that utilises haptic data to quantise the patient's performance. Two systems were implemented: a Fuzzy Inference System (FIS) and an Adaptive Neuro-Fuzzy Inference System (ANFIS). The two systems were validated with sample input/output datasets. Testing with real subjects' data has led to the conclusion that the CyberForce system is incapable of providing normative data for evaluating the patient performance due to calibration and consistency issues.

Original languageEnglish (US)
Pages (from-to)197-214
Number of pages18
JournalInternational Journal of Advanced Media and Communication
Issue number1-2
StatePublished - 2009


  • ANFISs
  • Adaptive neuro-fuzzy inference systems
  • Cyberforce
  • Fuzzy logic
  • Haptics
  • JTHF
  • Jebsen test of hand function
  • OT
  • Occupational therapy
  • Rehabilitation
  • Stroke

ASJC Scopus subject areas

  • Cultural Studies
  • Communication


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