## 4 Discussion
Collectively, the integration of gait tube analysis with these additional metrics provides a more comprehensive understanding of stability dynamics, suggesting that future exoskeleton designs should target phase-specific torque modulation to mitigate variability spikes while balancing metabolic efficiency, particularly in populations with heightened fall risk where such variability may be more pronounced [53; 54]. The visualization capabilities of gait tube analysis further enhance its clinical relevance. As shown in Figure 1, ellipsoids during unstable phases expand visibly in powered conditions, highlighting periods of instability. This visual language is more intuitive than abstract stability metrics and could support real-time feedback, gait retraining, or rehabilitation planning in neurologic populations. In summary, the gait tube framework complements and improves upon traditional stability metrics. It provides clinicians and researchers with a clear, time-resolved, multi-dimensional tool for evaluating the effects of assistive devices like exoskeletons on gait. These insights could guide the development of phase-specific controllers, tailor training to individual stability needs, and enable more precise interventions across clinical and performance settings. The phase-specific variability patterns identified in this study have important clinical implications. Individuals with impaired balance, such as stroke survivors or people with Parkinson's disease, may be more vulnerable to destabilizing effects during early stance when vertical variability is elevated. By integrating gait tube metrics into real-time control strategies, exoskeletons could be designed to modulate torque in a stability-aware manner, enhancing support during phases prone to instability while minimizing unnecessary assistance elsewhere. This approach could improve safety and confidence during walking in clinical populations, potentially reducing fall risk and supporting more personalized rehabilitation protocols. Several limitations should be considered when interpreting these findings. First, the sample size (n = 10) limits the generalizability of the results, particularly to clinical populations with varying gait patterns and stability impairments. Second, data were collected during treadmill walking, which may constrain natural variability compared to overground gait due to fixed belt speed and the absence of optic flow [30]. Third, the mass of the exoskeleton (5.77 kg) may have contributed to the observed variability through added inertia or mechanical constraint, particularly in the PowerOff condition [4]. Fourth, the adaptation period per condition was relatively short (-4 min), potentially limiting participants' ability to adjust their gait strategy fully [4]. Finally, the study focused on healthy adults; future research should extend this approach to clinical populations to determine how assistive torque influences pathological gait stability [11]. Future work should extend gait tube analysis to populations with known balance deficits, such as individuals with stroke, Parkinson's disease, or aging-related instability, where its high-resolution, phase-specific insights could uncover compensatory patterns or early markers of fall risk. Studies have shown that in these populations, increased gait variability often correlates with higher metabolic cost, reflecting inefficient compensatory strategies that compromise stability [53; 54; 55]. For instance, stroke survivors exhibit elevated energy expenditure alongside irregular gait patterns, which may predict fall risk [53]. Similarly, individuals with Parkinson's disease show heightened step timing variability, associated with increased metabolic demand and reduced dynamic stability [56]. In older people, greater stride variability is linked to higher walking energy costs, underscoring the need for precise stability metrics like gait tubes to optimize assistive interventions [57].