# Evaluation of Two Self-Fitting User Interfaces for Bimodal CI-Recipients
## 5 Discussion  
Overall, the study showed that all participants were able to make adjustments to their hearing with both of the self-fitting user interfaces. There was also no evidence of an effect of participant age or duration of hearing aid use. During the self-fitting, as well as afterwards, there were no indications from the participants that they had difficulties with the fitting. This statement is supported by the data on the self-fitting behavior in Section 4.2. Therefore, no further investigation was conducted in this regard. In the test-retest procedure, the statements of [PERSON] et al. (2011) and [PERSON] et al. (2017), that participants were able to make reproducible settings with the help of the 2D-Surface UI, was confirmed. Furthermore, a significant correlation was also observed with the help of the Equalizer UI. It became apparent that, for both UIs, parameters were present that were significantly different for each of the seven acoustic environments, indicating the need for situation-specific MAP-settings for different acoustic scenarios. Furthermore, the high dispersion of data within a given condition indicates how individual the respective settings were. For example, a clear pattern in the frequency adaptation of all participants within a particular condition could not be clearly identified. This finding goes hand in hand with the data from the study by [PERSON] et al. (2016) and shows how useful it is to make it possible for CI recipients to independently perform a situation-dependent fitting. The existing correlation between the endpoints of the CI and HA settings for the parameters bass, mid, and treble may indicate that a homogeneous sound image was set with the expert setting on both sides, which is coherent in itself but does not necessarily correspond to the personal taste of the participants. This means that only an adaptation to personal taste took place, and therefore the tendency of the settings was the same on both sides. However, no significant correlation was present for the volume parameter. This may be because less attention was paid to the homogeneous volume perception of both devices when creating the expert fit. This probably resulted in an adjustment of the volume by the participants themselves, which led to contrasting settings. However, independently of the side, it can be noted that, during the adjustment process, the areas with the most activity often went hand in hand with the end positions. This leads to the conclusion that a wide range of parameters were initially checked, but that a preferred range was quickly found, within which fine adjustments were subsequently made. The averaged endpoints, as well as the peaks of the averaged KDE in Figures 7 and 8, were often centrally located in the parameter space. The lowest values for the \(KDE_{mem}\) were frequently located in the peripheral areas of this space, but still far enough away from the overall boundaries, which leads to the conclusion that the parameter space provided was sufficiently large. [PERSON] et al. (2017) previously showed that self-fitting can be realized very quickly by participants with the 2D Surface UI. This can be confirmed by comparing the data in Figure 9, where it becomes apparent that an adjustment with the 2D Surface UI took significantly less time than an adjustment with the EQ UI. This aspect of a faster adjustment with the 2D Surface UI, while maintaining satisfaction with the self-fitting itself (see Section 4.5), must be considered when selecting a user interface for subsequent studies or clinical practice. This time saving can be attributed to a faster familiarization with the 2D-Surface UI but also to the fewer controls; instead of four sliders, only one point can be moved around. The data from the reliability test support this statement of a faster acclimatization and a lower training effect for the 2D-Surface UI. While the EQ UI had a significantly shorter duration in the retest, the 2D Surface UI needed almost the same time as in the first run.