Fine motor skills predict performance in the Jebsen Taylor Hand Function Test after stroke

Kathrin Allgöwer, Joachim Hermsdörfer

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Objective To determine factors characterizing the differences in fine motor performance between stroke patients and controls. To confirm the relevance of the factors by analyzing their predictive power with regard to the Jebsen Taylor Hand Function Test (JTHFT), a common clinical test of fine motor control. Methods Twenty-two people with slight paresis in an early chronic phase following stroke and twenty-two healthy controls were examined. Performance on the JTHFT, Nine-Hole Peg Test and 2-point discrimination was evaluated. To analyze object manipulation skills, grip forces and temporal measures were examined during (1) lifting actions with variations of weight and surface (2) cyclic movements (3) predictive/reactive catching tasks. Three other aspects of force control included (4) visuomotor tracking (5) fast force changes and (6) grip strength. Results Based on 9 parameters which significantly distinguished fine motor performance in the two groups, we identified three principal components (factors): grip force scaling, motor coordination and speed of movement. The three factors are shown to predict JTHFT scores via linear regression (R2 = 0.687, p < 0.001). Conclusions We revealed a factor structure behind fine motor impairments following stroke and showed that it explains JTHFT results to a large extend. Significance This result can serve as a basis for improving diagnostics and enabling more targeted therapy.

Original languageEnglish
Pages (from-to)1858-1871
Number of pages14
JournalClinical Neurophysiology
Volume128
Issue number10
DOIs
StatePublished - Oct 2017

Keywords

  • Fine motor control
  • Grip force
  • Prediction
  • Stroke

Fingerprint

Dive into the research topics of 'Fine motor skills predict performance in the Jebsen Taylor Hand Function Test after stroke'. Together they form a unique fingerprint.

Cite this