## 6 Conclusions
### Limitations and Future Work  
While this study provides meaningful insights into gesture-based interactions across TV and XR environments, several limitations must be acknowledged. First, the limited sample size in this study may pose a constraint on the generalizability of the findings. While the experiment yielded meaningful insights into gesture-based interactions across two interface environments, the relatively small number of participants may not adequately represent the broader user population. In particular, this study did not account for heterogeneity among user groups, such as variations in an expanded age span, technical and non-technical users, and cultural backgrounds. These factors may influence the broader applicability of the results to real-world gesture interaction scenarios, particularly in spatial computing contexts. As discussed in Section 5.4, future research should strive to incorporate more demographically and culturally diverse participant groups to enhance the ecological validity and inclusivity of the results. Second, although the experiment included a variety of gesture types and interaction environments, its scope was limited to only two specific platforms--TV and XR--with a relatively small number of core interaction tasks. This narrow focus may restrict the extent to which the findings can be generalized to broader application domains such as desktops,mobile interfaces, or in-vehicle infotainment systems. Each of these platforms presents unique interaction constraints and affordances that may significantly alter the effectiveness and usability of gesture inputs. Therefore, future studies should consider expanding the use testing across more diverse interface platforms to assess how gesture interactions could be applied and translated depending on user scenarios. Third, the experiment utilized a smart ring mockup rather than a fully operational device. Although the participants wore the ring as if it were functioning, the system was operated using a Wizard-of-Oz method, where a trained researcher manually interpreted the participants' gestures and triggered the corresponding responses behind the scenes. While this approach ensured high accuracy and minimal errors during the experiment, it did not fully capture the potential technical limitations of a real-time, sensor-based smart ring system--such as the gesture recognition latency, misdetections, or hardware-induced user discomfort. For instance, a delay of approximately 400 milliseconds in hand pose tracking has been reported for Ring-a-Pose [44]. Although seemingly minor, such latency could be perceptible to users and may result in a degraded sense of system responsiveness, thereby negatively affecting the overall user experience [86]. Moreover, the miniaturized batteries, sensors, and wireless communication modules in wearable devices can generate heat during their continuous operation, potentially causing discomfort for users [87]. Therefore, further studies using actual working hardware are necessary to validate the findings under realistic usage conditions. Lastly, while the interviews provided rich qualitative insights, they were conducted in a semi-structured format and involved only post-task reflections. This approach may have overlooked the real-time cognitive processes that occurred during interaction. Incorporating think-aloud protocols during the actual task execution could have provided more immediate and nuanced data, revealing the participants' situational reasoning, confusion, or momentary judgements. Building upon the insights and limitations outlined above, several directions for future research are proposed. First, future studies could explore a broader range of platforms and usage contexts, such as mobile AR, automotive interfaces, or multi-device ecosystems, to evaluate how the gesture interaction preferences shift across device ecologies and user scenarios. Second, the gesture taxonomy could be expanded further and refined by incorporating adaptive or personalized gestures.