## 8 Limitations and Future Work  
The primary limitations of this paper are that the resolution in which the quaternions were saved was not in high enough resolution to afford the calculation of jerk to a precise enough extent and that the sample size of 28 may not afford substantial extrapolative power. However, we believe that the work presented herein is valuable in that it both provides researchers with a roadmap and lessons learned for the calculation of angular jerk in AR/VR systems while also providing background literature that supports its application in these domains and providing examples of possible use cases. Another methodological limitation of the study was the short exposure time of two minutes per trial and the overall elapsed time the user spends wearing the HWD. These short exposure times may not have been enough time to elicit the performance and fatigue decrements seen in prior research [2,10] given that other studies have used longer exposure times with greater required levels of physical exertion [14]. Additionally, the narrow structure of the bridge and the random placement of the targets may have allowed users to see the entirety of the structure without needing to move their head at levels required to experience the negative effects of prolonged jerk exposure. Researchers wanting to conduct studies in this area should consider designing studies in a way that emphasizes distance between targets while making sure that the user is under significant time pressure to complete the task so that they are forced to make more exaggerated movements throughout the task. Doing so may better elucidate the potential effects of jerk in AR/VR systems relative to the signal detection task used in this work. Given the limitations of the present study, future work in this space should determine what levels of jerk and what cumulative exposure amounts elicit the greatest amount of physical fatigue and performance decrements in users so as to better understand how user movements while using AR and VR systems influence overall functioning and performance. Understanding these exposure factors will not only give designers and researchers better tools to understand how jerk in AR and VR interfaces can harm users, but can also help interface designers come up with new design paradigms that limit said exposures using methods like adaptive user interfaces. While much of the previous research using jerk has focused on the precipitous performance decrements associated with excessive loads caused by jerk, the work presented herein was unable to do so to a similar extent due to the lack of fidelity with the recorded quaternions and short exposure time. Instead, we focused mainly on providing researchers with an example application and calculation of the angular jerk metric so that researchers may apply this method to their experiments and develop targeted research designs that can better determine the long-term effects of excessive jerk in AR and VR. Critical to the widespread adoption and success of any product or device is in understanding how users interact with and are affected by the design. Thus, as AR and VR use becomes more ubiquitous and the technology underpinning these devices advances, it will be necessary to measure the effectiveness of these new technologies and use cases to understand how their design impacts users so that only the most appropriate designs are chosen to solve the novel challenges they will be designed to alleviate. While many measurement tools currently exist that aim to measure usability in its different forms, few are designed to measure the movement requirements of a given candidate HWD. Given that excessive jerk is a known issue in other similar human-technology systems, we hope that the work described herein will be used as a first step in that direction of creating holistic usability metrics for AR/VR interfaces and environments that can create new measurement paradigms that better explain and document how humans interact with augmented and virtual environments.