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(a_{mathrm{FEWT}_{t}}^i) denotes classification accuracy of ith feature selection method in combination with FEWT feature extraction method for tth task combination.
(22 Then the average (over all task combination) percentage gain in accuracy for sth technique is given by begin{aligned} P_{mathrm{FEWT}}^{i}=frac{1}{n_t}sum _{t=1}^{n_t}P_{mathrm{FEWT}_{t}}^i, quad forall i=0,1,2,...,n_s end{aligned}.
Wollesen and Voelcker-Rehage 24 performed a systemic review of the dual-task literature to examine the effects of specific versus general training and task combination on dual-task performance.
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Overall task performance was not affected by rTMS, whereas changes in task performance over time were disrupted according to TMS site and task combinations.
The impact of specific task combinations on dual-task performance has been widely discussed.
Chu et al 30 assessed the predictive value of different task combinations for predicting falls.
Both single-task and dual-task approaches were used, and dual-task training incorporated various task combinations.
Some task combinations required mainly mathematical skills for the cognitive task 26, 27, 52 whereas others required verbal and memory skills 41 or auditory skills.
While the current research suggests that a variety of trained task combinations can improve dual-task performance, future studies should compare how different combinations of tasks impact the efficacy of training.
In the studies that trained dual-task postural control, some assessed the efficacy of the intervention using trained task combinations 40 while others measured at least one novel task.
26, 27, 33– 37, 38, 38 The interventions that directly trained dual-task postural control employed a variety of task combinations with different levels of difficulty in the postural control and concurrent cognitive or motor tasks.
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