Most manual tasks comprise a sequence of action phases. Skill acquisition in such tasks involves a transition from reactive control, whereby motor commands for the next phase are triggered by sensory events signaling completion of the current phase, to predictive control, whereby commands for the next phase are launched in anticipation of these events. Here we investigated gaze behavior associa...

the aim of this study was to evaluate the effect of handedness and two practice types (explicit vs. implicit) on motor sequence learning. 60 girls (age range of 14 – 17 years old) were randomly assigned to four groups according to their handedness: right–handed-explicit, right–handed–implicit, left–handed-explicit, and left–handed-implicit. participants’ task was accuracy and time of sequential...

normative feedback is a kind of feedback which involves information about an individual's performance in comparison with other peers unrealistically (positive or negative). the aim of the present study was to determine the effect of normative feedback on throwing aiming task learning in children aged between 9 and 11 in ahvaz city. for this purpose, 90 right-handed children were selected w...

BACKGROUND Surgical interventions are complex, which complicates their rigorous assessment through randomised clinical trials. An important component of complexity relates to surgeon experience and the rate at which the required level of skill is achieved, known as the learning curve. There is considerable evidence that operator performance for surgical innovations will change with increasing e...

The present research examined two variables regarding the acquisition of a new bimanual coordination pattern: the role of previous experience and the nature of augmented feedback. Two groups of participants acquired a new coordination pattern (135 degrees relative phase) following two sessions of practice of another novel pattern (90 degrees relative phase). Transfer of learning in these groups...

In this paper, we propose a discriminative learning-based method for recovering the depth of a scene from multiple defocused images. The proposed method consists of a discriminative learning phase and a depth estimation phase. In the discriminative learning phase, we formalize depth from defocus (DFD) as a multi-class classification problem which can be solved by learning the discriminative met...