The capture and analysis of HRV data is central to this research. The emW (emW) uses photoplethysmography (PPG) to capture and record HRV data. PPG HRV devices are becoming readily available for a variety of applications; however, their use for research purposes remains a topic of some debate. Study One validated the emW against an Electrocardiogram (ECG) to ensure the validity of later studies in support of this research thesis. Five minutes of participant (n = 15) resting HRV data were simultaneously recorded using both an ECG and an emW. ECG R-R Interval data and time measures, and emW R-R Interval .txt files were imported into Graphpad Prism software (version 7) for R-R Interval overlay plots, Bland-Altman analysis, Linear Regression Analysis and t-test analysis. Bland-Altman analysis identified a generally good agreement between the ECG and emW R-R interval data. Eleven data sets showed good agreement: four data sets showed a bias of <.0001 ms, and a further nine data sets were <.01. The findings of this study suggest that the emW can be used in HRV research applications, if the researcher is fully informed of the strengths and limitations of the device.
Study two sought to further validate the emW as a suitable instrument to detect the difference in two different cognitive processes associated with two different cognitive tasks as measured by HRV. Condition A was a Go/NoGo working memory task, and Condition B was a sustained attention Spatial Reasoning task. The order of the Condition A and Condition B tasks was counterbalanced across participants (n = 15) by alternating the order in which each successive participant completed the Condition A and Condition B tasks. Significant effect was found for two HRV measures when analysing resting HRV, Condition A, and Condition B tasks. Of particular note, subsequent analysis of HRV when analysing resting HRV, Condition A task practice session and Condition B identifies significant difference in six HRV measures between both resting HRV and the Condition A task, and between the Condition A and Condition B tasks. These results suggest that HRV data acquired by the emW can differentiate between a person’s resting state, undertaking an intuitive decision-making task, and completing a deliberate problem solving task. The results also suggest that HRV is susceptible to changes in cognitive approach during task conduct. The different results for Condition A and Condition A practice suggest task familiarity changes the cognitive approach of a participant: this is an important finding given the nature of the research thesis and the context of military decision-making for the soldier undertaking a peace keeping or combat patrol.
The Third study examined an intervention that trains a person to mediate their HRV. To investigate if this program can improve a person’s resting HRV, and if any improvement in resting HRV is associated with improved performance in a decision-making task under conditions of no stress and mild stress. The absence of significant effect for group (Control group and Intervention group) across HRV measures suggests that the Intervention Program did not have an effect on the resting HRV of the intervention group participants: however, the reason for this is most likely that many of the participants didn’t commit to practicing the techniques.
The significant effect for condition (no stress and stress) in both HRV measures and game scores supports much earlier research that decision-making is degraded under conditions of stress. Whilst this is not a new finding, the nature of the decision-making task used in this study suggests an important line of inquiry in the conduct of decision-making under stress research. Currently there is some divide between decision-making research conducted in experimental settings, and decision research conducted in naturalistic settings. The challenge with naturalistic settings is establishing reliable and valid measures of decision-making. Many naturalistic decision-making research relies on self-report, or subjective measures of decision success. Studies conducted in experimental settings tend to be further removed from real life decision-making situations. The results from this study suggest that a middle ground can be found, allowing for valid and reliable collection of quantitative data for both physiological factors and for decision-making success.
The combined results of the three studies inform decision-making in the military environment. In particular the findings confirm the complex relationship between cognition and physiology, whilst also accounting for the ecological factors that influence the decision maker. This research is novel in that it combines these three elements, and it does so in the context of military decision-making.
|Qualification||Doctor of Philosophy|
|Award date||01 Mar 2018|
|Place of Publication||Australia|
|Publication status||Published - 2018|