Mohamed Boutaayamou

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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)
OBJECTIVE Gait disturbances like shuffling and short steps are obvious at visual observation in patients with advanced Parkinson's disease (PD). However, quantitative methods are increasingly used to evaluate the wide range of gait abnormalities that may occur over the disease course. The goal of this study was to test the ability of a trunk accelerometer(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)
In this paper, a finite element (FE) procedure for modeling electrostatically actu-ated MEMS is presented. It concerns a perturbation method for computing electrostatic fielddistortions due to moving conductors. The computation is split in two steps. First, an un-perturbed problem (in the absence of certain conductors) is solved with the conventional(More)
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