Fig 1.
Example of four types of submovements at 20 cm as defined by Chua and Elliott [6]’s algorithm.
The different columns indicate types of submovement in displacement, velocity and acceleration profiles (from left to right: none, pre-peak velocity, post-peak velocity, undershoot, and overshoot). The solid line indicates zero level for the respective variable.
Fig 2.
The average number of trials as a function of number of submovements (1 = only primary movement, 2 = primary movement with secondary submovement etc.) in a trial for different movement space-time conditions.
Top row indicates 10 cm, middle row shows 20 cm, and bottom row is 30 cm movement amplitude. The error bars represent the between-participant standard deviation. The upper middle of each graph shows the mean movement time for each space-time condition.
Fig 3.
The average number of submovements for 3 different amplitudes as a function of space-time conditions.
The error bars represent the between-participant standard deviation.
Fig 4.
The distributions of different submovement types (N = none, Pr = pre-peak, Po = post-peak, U = undershoot, and O = overshoot) for the 5 space-time conditions (fast, fast-mid, middle, mid-accurate, and accurate).
The different rows indicate different movement amplitudes (10, 20 and 30 cm). The error bars are the between-participant standard deviation.
Table 1.
Statistical results for incidence of submovement types (post hoc simple main effect analyses).