# Leader-Follower Role Allocation for Physical Collaboration in Human Dyads
## 4 Discussion  
The goal of this study was to observe the leader-follower dynamics in dyadic interactions and to evaluate whether these dynamics can be predicted in a dyad based on the individual performance of the partners. We hypothesised that the influence of each partner is not equally shared, but rather that the subject displaying higher performance in individual tasks influences the collaborative task performance more, thus assuming the leader role in a dyad. Furthermore, we hypothesised that the definition of higher-performing and lower-performing subject in individual tasks will influence how the leader-follower dynamics will be predicted in the collaborative task. Based on [18] we additionally hypothesised that the performance of subjects will improve when in collaboration compared to their individual performance. In this study we showed that in each collaboration one partner has more influence on the task performance than the other, meaning that the partner actively assumes the role of a leader. We have also shown that the leader-follower dynamics can be predicted based on  
Figure 5: Task performance of individual subjects and subjects in collaboration for (**a**) whole experiment and for (**b**) each target separately. The task performance for each experiment is defined using Fitts’ law index of performance (IP), where the performance is better with higher values. Note that \(*\) denotes significant statistical difference and \(\diamond\) denotes no statistical difference. the subjects' individual performance, as the higher performing subject in individual tasks will most likely assume the role of a leader. _Determining the higher-performing and lower-performing subject:_ When comparing the results from different sorting methods used to define the higher-/lower-performing individuals, we have found that using any of the selected metrics to sort the partners before defining the leader will produce similar results with an increase or decrease in the standard errors of mean (SEM) and the number of dyads that have the same result as the average. The differences in SEM are due to the fact that subjects in some dyad switch their role as the higher-performing or the lower-performing partner based on the sorting method used. These differences show that the definition of the higher- and lower-performing individual is important when trying to predict the leader-follower dynamics in a collaborative task. Due to this, the method used to define the higher- and lower-performing individual should be taken into account when determining the accuracy and reliability of our predictions. Here, results presented in Figure 3 suggest that the most reliable metric from the ones used is the maximum velocity in task performance as it has the lowest SEM. The lowest SEM can be explained as the fact that in the haptic interface used in this study and described in [19], the velocity directly correlates to the amount of force exerted by each individual when performing the task. When an individual with higher maximum velocity performs the task using the proposed haptic interface, they use a larger amount of force than the individual with lower maximum velocity. As the haptic interface is controlled through the use of force, the individual with a larger force exertion will have more influence over the control of the haptic interface, thus assuming the role of leader. It is worth noting, however, that although maximum velocity was decided as the most reliable metric based on its lowest SEM, other metrics on average also produce the same result--predicting the higher-performing individual as the leader. This can be explained as the selected metrics used to define the higher-/lower-performing individuals are correlated with each other. For instance, IP is directly defined by the measured time, while measured time directly depends on the subject's velocity.