A unifying conceptual framework of factors associated to cardiac vagal control

Laborde, Sylvain; Mosley, Emma; Mertgen, Alina

doi:10.1016/j.heliyon.2018.e01002

Cited by 47 publications

(62 citation statements)

References 284 publications

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“…Neuroscience research has documented that individuals with a high tonic activity (vagal baseline at resting) are associated with better cognitive performance and adaptation to stressful environments [27,[29][30][31][32][33]. By contrast, individuals who have low tonic activity show lower cognitive performance and they presented a lack of adaptation in stressful situations [27,32,76].…”

Section: Vagal Activitymentioning

confidence: 99%

“…The vagus nerve is the main nerve of the parasympathetic nervous system and its activity is identified as vagal tone. The vagal tone could be monitoring efficiently by the Heart Rate Variability (HRV) and its measure is related to emotional state, cognitive performance and health status [29][30][31]. These models show that a higher vagal tone, reflected by high HRV, represents better emotional self-regulation, executive functioning (e.g.…”

mentioning

confidence: 99%

“…Inversely a lower vagal tone, reflected by low HRV has been associated to a poor emotional self-regulation (e.g. rigid, fear, treat, hypervigilance), a decline of executive functions and health impairments [29][30][31][32].…”

mentioning

confidence: 99%

“…This low tonic activity is also related to prefrontal cortex inhibition (low executive functions, lack of attention, working memory impairment) as well as an amygdala hyperactivity (increasing threat and fear perception, hypervigilance). By contrast, healthy vagal function has been related to better prefrontal control over an inhibition of amygdala function, resulting in a better adaptation to stressful situations [27,[29][30][31][32][33]. For example, it was observed by Hansen et al [34] among a cohort of sixty-five military navy sailors, divided into low HRV and high HRV groups, that the group with low HRV had worse performance to cognitive tasks (i.e.…”

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confidence: 99%

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Exploring the relationship between health status and simulated patient-care scenario performance among experienced paramedics.

Tremblay¹,

Wj²,

Sl³

et al. 2020

Preprint

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BACKGROUND: It is well known that health status of paramedics may be altered by their job demands. However, it is unknown whether health conditions have a negative impact on occupational performance. The goal of this study was to explore whether a paramedic’s health status affects performance during a patient-care simulation. More precisely, this paper aims to identify which health conditions (i.e., cardiovascular diseases (CVD), musculoskeletal disorders (MSD), post-traumatic stress disorders (PTSD), generalized anxiety disorders (GAD)) could be associated with negative performance. METHODS: Nineteen paramedics aged 38.2 ± 8.6 years old with 15.0 ± 8.7 years of paramedic experience participated in this study. Participants completed two assessments: i) health conditions measurements and ii) patient-care simulation. Heart rate variability (HRV), an indicator of vagal activity was collected during the patient-care simulation. The simulation was used in order to challenge experienced paramedics in a realistic setting. Based on the provincial standard of New Brunswick, an experienced paramedic instructor graded (passed or failed) the patient-care simulation using the provincial standard charts, videos and data from manikin. RESULTS: The current study suggests that only paramedics with self-reported elevated symptoms of PTSD were less likely to successfully complete the simulated patient-care scenario. An inhibition of the vagal activity was noted during the patient-care simulation among individuals identified with PTSD. No link was observed between physical health conditions (CVD, MSD) and simulated patient-care performance. Overall, paramedics who passed the patient-care simulation presented higher vagal activity during the patient assessment. CONCLUSIONS: This research suggests that the presence of self-reported elevated symptoms of PTSD negatively impacts paramedics’ performance during a stressful work task simulation. Therefore, to help paramedics maintain optimal performance, it may be important to ensure that paramedics have access to appropriate resources to monitor and improve their psychosocial health. Future studies should investigate more complex work tasks with larger sample sizes and more complex simulations.

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Section: Vagal Activitymentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Exploring the relationship between health status and simulated patient-care scenario performance among experienced paramedics.

Tremblay¹,

Wj²,

Sl³

et al. 2020

Preprint

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“…Extensive research has been dedicated to understand and describe the complex interplay of factors that affect heart rate variability (HRV), the physiological phenomenon of the variation in the time interval between consecutive heartbeats. The dynamic task-specific vagal control of the heart represented by task-related HRV changes is especially valuable in exploring the flexible adaption of the organism to physical and mental challenges [1,2]. Age has been identified as the most critical variable affecting HRV, with the spectral power of HRV decreasing with increasing age [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Stochastic Modeling and Optimal Time-Frequency Estimation of Task-Related HRV

2019

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In this paper, we propose a novel framework for the analysis of task-related heart rate variability (HRV). Respiration and HRV are measured from 92 test participants while performing a chirp-breathing task consisting of breathing at a slowly increasing frequency under metronome guidance. A non-stationary stochastic model, belonging to the class of Locally Stationary Chirp Processes, is used to model the task-related HRV data, and its parameters are estimated with a novel inference method. The corresponding optimal mean-square error (MSE) time-frequency spectrum is derived and evaluated both with the individually estimated model parameters and the common process parameters. The results from the optimal spectrum are compared to the standard spectrogram with different window lengths and the Wigner-Ville spectrum, showing that the MSE optimal spectral estimator may be preferable to the other spectral estimates because of its optimal bias and variance properties. The estimated model parameters are considered as response variables in a regression analysis involving several physiological factors describing the test participants’ state of health, finding a correlation with gender, age, stress, and fitness. The proposed novel approach consisting of measuring HRV during a chirp-breathing task, a corresponding time-varying stochastic model, inference method, and optimal spectral estimator gives a complete framework for the study of task-related HRV in relation to factors describing both mental and physical health and may highlight otherwise overlooked correlations. This approach may be applied in general for the analysis of non-stationary data and especially in the case of task-related HRV, and it may be useful to search for physiological factors that determine individual differences.

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