System identification and modeling approach to characterizing rigidity in parkinson's disease: Neural and non-neural contributions

Ruiping Xia, Matija Radovic, Joseph Threlkeld, Zhi Hong Mao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Rigidity (muscle stiffness) is one of the most disabling symptoms in Parkinson's disease (PD). It is clinically defined as an increased resistance to passive movement of a joint. There is a fundamental gap between mechanistic and applied approaches to understanding this symptom. The objective of the current study was to apply a system identification and modeling approach to differentiating the contributions of neural (enhanced muscle reflex) and non-neural (altered mechanical properties of muscle fibers) factors to rigidity. Six patients participated in the study. The wrist joint torque and muscle activities of the wrist muscles were measured during externally induced movements. Each subject was tested in the Off- and Onmedication states. System identification and modeling approach was applied to separate the neural from the nonneural component with respect to the overall stiffness. Results show that both factors are responsible for rigidity in PD. Neural-related reflex component is the predominant factor in overall rigidity. Medication therapy decreased the level of reflex component to overall rigidity.

Original languageEnglish
Title of host publication2010 4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010
DOIs
Publication statusPublished - 2010
Event4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010 - Chengdu, China
Duration: Jun 18 2010Jun 20 2010

Other

Other4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010
CountryChina
CityChengdu
Period6/18/106/20/10

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All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics

Cite this

Xia, R., Radovic, M., Threlkeld, J., & Mao, Z. H. (2010). System identification and modeling approach to characterizing rigidity in parkinson's disease: Neural and non-neural contributions. In 2010 4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010 [5514861] https://doi.org/10.1109/ICBBE.2010.5514861