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Abstract :
[en] We present a new signal processing algorithm that extracts
five gait events: heel strike, toe strike, heel-off, toe-off, and heel clearance
from only two accelerometers attached on the heels of the subjects
usual shoes. This algorithm first uses a continuous wavelet-based segmentation
that parses the signal of consecutive strides into motionless
periods defining relevant local acceleration signals. Then, the algorithm
uses versatile techniques to accurately extract the five gait events from
these local acceleration signals. We validated, on a stride-by-stride basis,
the extraction of these gait events by comparing the results with reference
data provided by a kinematic 3D analysis system and a video camera.
The accuracy and precision achieved by the extraction algorithm for
healthy subjects, the reduced number of accelerometer units required,
and the validation results obtained, encourage us to further study this
system in pathological conditions.
Research Center/Unit :
Laboratoire d'Analyse du Mouvement Humain (LAMH) / Signal and Image Exploitation (INTELSIG) - University of Liège, Liège, Belgium
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