Figure 3.

Segment-based evaluation. The true label was assigned to each segment based on the temporal relationship to a movement onset. Since we observed highly subject-specific differences of the time when a movement can be predicted before the actual movement onset, we used the following dynamic method to determine whether the true class of a segment is the movement or rest. In all cases the segments ending at $-80$ or $-40$ ms relative to the movement onset were expected to predict a movement (i.e., belong to the movement class, denoted as pre-movement phase). All segments ending in the interval $[-1$ s,$\dots ,-120$ ms] were further investigated whether they belong to a consecutive sequence of predictions of the movement class with at most one exceptional case (pre-movement unknown phase). All segments ending between the movement onset and the end of the movement plus an additional tolerance period of 200 ms were not included in the performance evaluation (post-movement phase). All remaining segments were assigned to the resting class. For training of the classifier, the segments ending in the interval $[-120,\dots ,120]$ ms were used as examples for the movement class, all remaining segments (apart from examples ending in the in-movement phase) were used as examples for the resting class.