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Systematic Review on the Applicability of Principal Component Analysis for the Study of Movement in the Older Adult Population.

Juliana Santos MoreiraBruno SilvaHugo FariaRubim SantosAndreia S P Sousa
Published in: Sensors (Basel, Switzerland) (2022)
Principal component analysis (PCA) is a dimensionality reduction method that has identified significant differences in older adults' motion analysis previously not detected by the discrete exploration of biomechanical variables. This systematic review aims to synthesize the current evidence regarding PCA use in the study of movement in older adults (kinematics and kinetics), summarizing the tasks and biomechanical variables studied. From the search results, 1685 studies were retrieved, and 19 studies were included for review. Most of the included studies evaluated gait or quiet standing. The main variables considered included spatiotemporal parameters, range of motion, and ground reaction forces. A limited number of studies analyzed other tasks. Further research should focus on the PCA application in tasks other than gait to understand older adults' movement characteristics that have not been identified by discrete analysis.
Keyphrases
  • systematic review
  • physical activity
  • case control
  • meta analyses
  • randomized controlled trial
  • high resolution
  • mass spectrometry
  • community dwelling
  • data analysis