Inverse dynamics modelling of upper limb tremor, with cross-correlation analysis.

Laurence P Ketteringham, David Western, Simon A Neild, Rick A Hyde, Rosemary Jones, Angela Davies Smith

Research output: Contribution to journalArticle (Academic Journal)peer-review

4 Citations (Scopus)
364 Downloads (Pure)

Abstract

A method to characterise upper-limb tremor using inverse dynamics modelling in combination with cross-correlation analyses is presented. A 15 degree-of-freedom inverse dynamics model is used to estimate the joint torques required to produce the measured limb motion, given a set of estimated inertial properties for the body segments. The magnitudes of the estimated torques are useful when assessing patients or evaluating possible intervention methods. The cross-correlation of the estimated joint torques is proposed to gain insight into how tremor in one limb segment interacts with tremor in another. The method is demonstrated using data from a single patient presenting intention tremor because of multiple sclerosis. It is shown that the inertial properties of the body segments can be estimated with sufficient accuracy using only the patient’s height and weight as a priori knowledge, which ensures the method’s practicality and transferability to clinical use. By providing a more detailed, objective characterisation of patient-specific tremor properties, the method is expected to improve the selection, design and assessment of treatment options on an individual basis.
Original languageEnglish
Pages (from-to)59-63
Number of pages5
JournalHealthcare Technology Letters
Volume1
Issue number2
Early online date27 May 2014
DOIs
Publication statusPublished - Jun 2014

Keywords

  • diseases
  • biomechanics
  • torque
  • patient treatment
  • multiple sclerosis
  • cross-correlation analysis
  • limb motion
  • body segments
  • joint torques
  • intention tremor
  • inverse dynamics modelling
  • upper limb tremor
  • inertial properties

Fingerprint

Dive into the research topics of 'Inverse dynamics modelling of upper limb tremor, with cross-correlation analysis.'. Together they form a unique fingerprint.

Cite this