Characterization of Upper-Limb Pathological Tremors: Application to Design of an Augmented Haptic Rehabilitation System

Seyed Farokh Atashzar, Mahya Shahbazi, Olivia Samotus, Mahdi Tavakoli, Mandar S. Jog, Rajni V. Patel

Research output: Contribution to journalArticlepeer-review


In this paper, an adaptive filtering technique is proposed to estimate and characterize pathological tremors caused by Parkinson's Disease (PD) and Essential Tremor (ET). The technique is based on the formulation of band-limited multiple Fourier Linear Combiners (BMFLC) and is called Enhanced-BMFLC (E-BMFLC). The effectiveness of the designed filter is statistically evaluated through a clinical study involving 14 PD and 13 ET patients. The hand tremors of the participants are studied in three Degrees Of Freedom (DOF). Using statistical analysis, it is shown that the new design of the filter significantly enhances the accuracy in comparison with the performance of conventional BMFLC filtering. In addition, E-BMFLC significantly reduces the sensitivity to parameter tuning and intrapatient variabilities. The observed improvements are achieved by modulating the memory of the proposed filter, and by enriching the utilized harmonic model. The proposed filter is then used to develop a safe haptics-enabled robotic rehabilitation architecture, designed for patients having hand tremors. The architecture is entitled Augmented Haptic Rehabilitation (AHR), which enables adaptive management of the involuntary components of the hand motion while delivering assist-as-needed haptic therapy (for the voluntary component) and avoiding unsafe amplification of hand tremors. Experimental evaluations are provided to evaluate the efficacy of the proposed AHR system.

Original languageEnglish (US)
Article number7407298
Pages (from-to)888-903
Number of pages16
JournalIEEE Journal on Selected Topics in Signal Processing
Issue number5
StatePublished - Aug 2016


  • Adaptive filters
  • assist-as-needed robotic rehabilitation
  • pathological hand tremors

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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