Owing to the multi-factorial nature of fatigue, leveraging context to effectively monitor and intervene with fatigue symptoms presents a significant challenge. This paper aimed to understand how to incorporate context into designing mHealth systems for fatigue management. We conducted a two-week field study with 20 fatigue-vulnerable individuals using an activity-tracking sensor and self-reporting. We conducted data-prompted interviews to explore phenomena about participants’ fatigue experiences. Findings show a heterogeneous relationship between context and fatigue, which can be attributed to the phenomena that: (1) participants were influenced by multiple fatigue-inducing factors for different durations; (2) broad contexts moderated participants’ perceptions and coping strategies in response to local contexts; (3) the predictability and repetition of activities influenced participants’ fatigue perception and coping strategies. We propose a context-informed layer-based framework integrating these phenomena and discuss implications for designing fatigue management tools informed by our framework.

In previous studies, researchers have successfully measured walking in healthy able-bodied humans to create safe control strategies for lower body assistive devices. measurements used to establish design requirements often come from testing and evaluation that takes place in laboratory settings during steady-state tasks, where participants often select movement strategies that minimize the cost of transport. However, human walking in these conditions does not neces-sarily represent the natural behavior of an individual in the real world. In this work, we conducted a study to characterize human walking in the real world. We combined week-scale free-living measurements of gait with in-lab data collection to: 1) quantify the proportion of steady-state walking in a population of healthy able-bodied adults, and 2) evaluate whether this population favors the selection of a range of walking speeds that minimize their cost of transport in the real world. We found that the majority of walking bouts contain mostly transient walking, suggesting that researchers should complement steady-state characterization with non-steady-state tasks. We also found that the most often used steady-state walking speeds for all participants were higher than the range that minimizes cost of transport, suggesting that individuals are influenced by more than energy economy when moving in the real world. Thus, when developing control strategies for these devices, researchers should consider a variety of optimization objectives to adapt for the multifarious situations of daily life.