Human Performance-Based Measurement System

Braun, Jeff; Lichtenstein, Eric; Lomg, Joe; Prell, Glenn Le; Henry, Martha

doi:10.21236/ada373062

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…Respiration rate, in particular, has been shown to be one of the best physiological markers of physical exertion and responds most readily to changes in work rate while also being sensitive to cognitive load and other psychological stressors (Massaroni et al, 2019;Nicolò et al, 2020). HRV, derived from heart rate readings, has also been shown to decrease with increased physical and mental stress (Porges and Byrne, 1992;Braun et al, 1999;Buijs, 2013). More recently, multiple authors have considered the potential value of additional processing of HRV data, including multiple entropy or other statistical measures, as providing capabilities to distinguish more critical health indicators, such as risk of arrhythmias (Liu et al, 2013;Dong, 2016;Karmakar et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Physiological Responses During Field Science Task Performance: Feasibility and Future Needs

Hill

Caldwell

2022

Front. Physiol.

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ObjectiveBy understanding the physiological demands of different types of tasks that will be performed during extravehicular activity (EVA) on Mars, human performance safety risks can be mitigated. In addition, such understanding can assist in planning EVAs with an appropriate balance of human health and safety with scientific mission return.BackgroundThis paper describes the results of a study of technical feasibility performed within a Mars human research analog, with participants conducting scientifically relevant planetary science sample analysis and return tasks in two distinct field locations.MethodsThe authors collected heart rate, respiration rate, and heart rate variability (HRV) data, using commercial off-the-shelf hardware and software from study participants as they performed field science tasks within a concept of operations for a Mars science return human expedition mission. These data were remotely monitored, shared in real time, and later analyzed to identify different responses to different tasks in order to determine if there were any predictable or consistent patterns among participants.ResultsIt was ultimately determined that, while differences exist between responses to tasks, they are highly subject to multiple sources of individual variability, dynamics of evolving field science tasks, and demands of a demanding physical environment. Further, distributional analyses of participants do not support parametric statistical analysis techniques.ConclusionThe authors conclude that the physiology of individual astronauts should be extensively studied and modeled to support individualized automated monitoring tools for each crew member that is sent to Mars. Application: Physiological monitoring for specialized populations will require significant individual-level analysis, baselining, and bootstrap statistical methods to enable appropriate human performance determinations.

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