Motor output complexity in Parkinson's disease during quiet standing and walking: Analysis of short-term correlations using the entropic half-life

C. Pasluosta*, J. Hannink, H. Gaßner, V. Von Tscharner, J. Winkler, J. Klucken, B. M. Eskofier

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

7 Citations (Scopus)

Abstract

Parkinson's disease (PD) is associated with alterations in motor outputs such as center of pressure (CoP) adjustments during quiet standing and foot kinematics during walking. Previous research suggests that the complexity of motor outputs reflects the number of control processes stabilizing a specific movement, providing a measure that is linked to the neurological control of the movement. The Entropic Half Life (EnHL) represents a new method for assessing motor output complexity. We hypothesized that there will be a lack of neuromuscular control pathways for PD patients, resulting in a decrease in motor output complexity. We computed the EnHL of CoP adjustments during quiet standing and foot kinematics during walking of 70 PD patients and 33 age-matched controls. Patients with PD showed longer EnHL values compared to controls, suggesting a tighter motor control. Excluding vision led to a decrease of EnHL of CoP in both groups. EnHL was correlated with spatio-temporal gait parameters. We compared EnHL with the pull test and the timed up-and-go test. No significant differences were present in the pull test, yet motor output complexity was correlated with the timed up-and-go test. The results suggest a reduced complexity in motor outputs of PD patients affecting distinct motor functions.

Original languageEnglish
Pages (from-to)185-194
Number of pages10
JournalHuman Movement Science
Volume58
DOIs
Publication statusPublished - Apr 2018
Externally publishedYes

Keywords

  • Center of pressure
  • Complexity
  • Gait
  • Motor output
  • Parkinson's disease

Fingerprint

Dive into the research topics of 'Motor output complexity in Parkinson's disease during quiet standing and walking: Analysis of short-term correlations using the entropic half-life'. Together they form a unique fingerprint.

Cite this