Vincent Denoël

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An original signal processing algorithm is presented to automatically extract, on a stride-by-stride basis, four consecutive fundamental events of walking, heel strike (HS), toe strike (TS), heel-off (HO), and toe-off (TO), from wireless accelerometers applied to the right and left foot. First, the signals recorded from heel and toe three-axis(More)
BACKGROUND The contralateral shoulder is often used as a reference when evaluating a pathologic shoulder. However, the literature provides contradictory results regarding the symmetry of the scapular pattern in a healthy population. We assume that several factors including gender and type of motion may influence the bilateral symmetry of the scapulae. (More)
Populations considered for shoulder analysis are often composed of various ratios of men and women. It is consequently hypothesized that gender has no significant effect on the joint kinematic. However, the literature reports, for the shoulder, differences in the range of motion between genders. The specific influence of gender on the scapulo-thoracic(More)
In our aging society, gait disturbance becomes a major concern as it inevitably leads to limitations in mobility and to an increased risk of falls. Spontaneous walking speed normally decreases by about 1% per year from age 60 onward [1]. A population-based study has shown a 35% prevalence of gait disorders among persons over age 70 [2], and some abnormal(More)
A new signal processing algorithm is developed for quantifying heel strike (HS) and toe-off (TO) event times solely from measured heel and toe coordinates during overground walking. It is based on a rough estimation of relevant local 3D position signals. An original piecewise linear fitting method is applied to these local signals to accurately identify HS(More)
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