Cardiac sympathetic activity during recovery as an indicator of sympathetic activity during task performance

Abstract

The goals of this research were to analyze cardiac sympathetic recovery patterns and evaluate whether sympathetic cardiac responses to a task challenge can be predicted using residual cardiac activity measured directly after the task (that is, during the recovery period). In two studies (total N = 181), we measured cardiac sympathetic activity, quantified as pre‐ejection period and RB interval, during both task performance and the 2‐min recovery period following the task. Additional analyses examined effects on the RZ interval. We found that sympathetic recovery from a task was rather quick: Cardiovascular recovery occurred within the first 30 s of the recovery period. Nevertheless, residual cardiac activity during the recovery period had predictive power for task‐related cardiac activity. This suggests that sympathetic cardiac activity during recovery may serve as a useful indicator of task‐related cardiac sympathetic activity. We discuss the implications of these findings for practical applications and the design of future studies.

Association between PTSD and Impedance Cardiogram‐based contractility metrics during trauma recall: A controlled twin study

“…Previous studies examining HR and blood pressure (BP) changes during trauma recall are relatively nonspecific and unfortunately offer limited insight on specific diseases such as heart failure (Bauer et al, 2013; Castro‐Chapman et al, 2018; Katz et al, 2020; Pole, 2007; Wangelin & Tuerk, 2015). HR is influenced by both sympathetic and parasympathetic influences, whereas BP (systolic (SBP) and diastolic (DBP)) is affected by both cardiac contractility and total peripheral resistance (Czarnek et al, 2021). Also, the HRV metrics do not provide an independent SNS activity analysis.…”

Validation of a new impedance cardiography analysis algorithm for clinical classification of stress states

“…Our findings have important potential clinical applications and public health implications, which call for more research in this area. Accurate PEP examination with TEA may improve prediction of mortality in the general population (Medina‐Lezama et al, 2018), evaluation of early cardiovascular disease, management of hypertension (DeMarzo, 2020; Silva Lopes et al, 2019), and for assessing stress levels in persons with PTSD and monitoring autonomic function (Czarnek et al, 2021; Kelsey et al, 2007; Kibler, 2018; Malcolm et al, 2016; Meijer et al, 2011; Silvia et al, 2020).…”

“…Some authors found a noisy signal even for the recordings where participants were seated, while others do not find it problematic, and observed little noise. In general, small movements can induce noisy artifacts in the signal (Czarnek et al, 2021). For example, 22% of the ICG signal were identified as noisy in participants who were reading in a seated position (Cybulski et al, 2011).…”

“…A popular method to mitigate the noise in the ICG signal is ensemble averaging (EA; Czarnek et al, 2021; Kibler, 2018; Kizakevich et al, 1976; Malcolm et al, 2016; Silvia et al, 2020; Sornmo & Laguna, 2005), which we refer to as the “conventional EA algorithm” (CEA). In our prior work, we have improved upon this approach with an open‐source automated ICG noise removal algorithm − three‐stage EA algorithm (TEA; Sheikh, Shah, Levantsevych, et al, 2020).…”

Data‐driven approach for automatic detection of aortic valve opening: B point detection from impedance cardiogram

“…Impedance cardiogram (ICG) is the first‐order time derivative (dZ/dt) of the thoracic impedance signal (Z). Parameters and biomarkers derived using ICG have been found effective in the prediction of mortality in the general population (Silva Lopes et al, 2019), assessment of early cardiovascular disease (DeMarzo, 2020), management of hypertension (Medina‐Lezama et al, 2018), and evaluating cardiac autonomic functioning in stress studies (Cohen et al, 2020; Czarnek et al, 2021; Kelsey et al, 2007; Kibler, 2018; Malcolm et al, 2016; Meijer et al, 2011; Peters et al, 2018; Silvia et al, 2020). However, intra‐ and inter‐subject morphological variability of the ICG waveform coupled with noise sensitivity are the major limitations for reliable ICG‐based applications and have likely limited its use in research and clinical practice.…”