Objective real-time assessment of walking and turning in elderly adults.
Recent research suggests that falls are the most common cause of injury and disability in older persons. Invasive systems or body worn sensors can be employed in controlled clinical and laboratory settings to determine clinical measures of gait and stability. This study by contrast aims to explore how video technology, can be employed to unobtrusively determine the same measures. Data from 63 elderly subjects, recruited through a research clinic was analyzed. The derived parameters include: the walk time, the number of steps of the TUG test and stability out of the turn. The results show that video analysis can be used to automate current clinical measures of gait and stability as well as to inform future automated interventions.
Skrba
Zoran
Z
TRIL Centre, University College Dublin, Ireland. zoran.skrba@ucd.ie
O'Mullane
Brian
B
Greene
Barry R
BR
Scanaill
Cliodhna Ni
CN
Fan
Chie Wei
CW
Quigley
Aaron
A
Nixon
Paddy
P
D056044:Actigraphy / Q000379:methods*; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D029721:Drosophila Proteins; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D024101:Mitochondrial Proteins; D016138:Walking / Q000502:physiology*; D051598:Whole Body Imaging / Q000379:methods*
D029721:Drosophila Proteins; D024101:Mitochondrial Proteins; C504899:retm protein, Drosophila