Article

Gait variability may have greater utility than spatio-temporal parameters and
can, be an indication for risk of falling in people with Parkinson's disease
(PD). Current methods rely on prolonged data collection in order to obtain large
datasets which may be demanding to obtain. We set out to explore a phase plot
variability analysis to differentiate typically developed adults (TDAs) from PD
obtained from two 10 m walks. Fourteen people with PD and good mobility
(Rivermead Mobility Index>/=8) and ten aged matched TDA were recruited and walked
over 10-m at self-selected walking speed. An inertial measurement unit was placed
over the projected centre of mass (CoM) sampling at 100 Hz. Vertical CoM
excursion was derived to determine modelled spatiotemporal data after which the
phase plot analysis was applied producing a cloud of datapoints. SDA described
the spread and SDB the width of the cloud with beta the angular vector of the
data points. The ratio ( for all) was defined as SDA: SDB. Cadence (p=.342) and
stride length (p=.615) did not show a significance between TDA and PD. A
difference was found for walking speed (p=.041). Furthermore a significant
difference was found for beta (p=.010), SDA (p=.004) other than SDB (p=.385) or
ratio for all (p=.830). Two sequential 10-m walks showed no difference in PD for
cadence (p=.193), stride length (p=.683), walking speed (p=.684) and beta
(p=.194), SDA (p=.051), SDB (p=.145) or for all (p=.226). The proposed phase plot
analysis, performed on CoM motion could be used to reliably differentiate PD from
TDA over a 10-m walk.
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Langue : ANGLAIS