The sensitivity of 38 heart rate variability measures to the addition of artifact in human and artificial 24‐hr cardiac recordings

Stapelberg, Nicolas J. C.; Neumann, David L.; Shum, David; McConnell, Harry; Hamilton‐Craig, Ian

doi:10.1111/anec.12483

Cited by 31 publications

(31 citation statements)

References 66 publications

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“…Although previous studies have shown a possible correlation between the different measures [ 33 , 34 ], an exact equivalence has not been reported. It is possible that Poincaré plots may detect abnormalities that are not as easily detectable with traditional time-domain measures, given that each parameter has different sensitivity to noise and other experimental conditions [ 35 ]. Hence, further investigations to fully uncover and understand the physiological relevance of these autonomic assessment methods are warranted in order to determine the efficacy of the different metrics in accurately quantifying autonomic activity”.…”

Section: Discussionmentioning

confidence: 99%

Stochastic vagus nerve stimulation affects acute heart rate dynamics in rats

et al. 2018

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Vagus nerve stimulation (VNS) is an approved therapy for treatment of epilepsy and depression. While also shown to be promising in several preclinical and clinical studies to treat cardiovascular diseases, optimal therapeutic stimulation paradigms are still under investigation. Traditionally, parameters such as frequency, current, and duty cycle are used to adjust the efficacy of VNS therapy. This study explored the effect of novel stochastic VNS (S-VNS) on acute heart rate (HR) dynamics. The effect of S-VNS was evaluated in Sprague Dawley rats by comparing the acute HR and HR variability (HRV) responses to standard, periodic VNS (P-VNS) across different frequencies (FREQs, 10–30 Hz). Our results demonstrate that both S-VNS and P-VNS produced negative chronotropic effects in a FREQ-dependent manner with S-VNS inducing a significantly smaller drop in HR at 10 Hz and 20 Hz compared to P-VNS (p<0.05). S-VNS demonstrated a FREQ-dependent drop in the SD1/SD2 ratio, a measure of HRV, which was absent in P-VNS, suggesting that S-VNS may acutely modulate the nonlinear relationship between short- and long-term HRV. In conclusion, S-VNS is a novel stimulation procedure that may provide different physiological outcomes from standard P-VNS, as indicated by our analysis of HR dynamics. Our study provides a rationale for further detailed investigations into the therapeutic potential of S-VNS as a novel neuromodulation technique.

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Section: Discussionmentioning

confidence: 99%

Stochastic vagus nerve stimulation affects acute heart rate dynamics in rats

et al. 2018

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“…They primarily respond to the body's regulatory functions and are hypersensitive to noise from movement, changes in breathing rate and speech (Jorna, 1992;Young, 2000). We recorded heart activity and explored LF/HF ratio and standard deviation of inter-beat intervals, as they are related to mental workload and less affected by artifacts than other variability measures (Stapelberg, Neumann, Shum, McConnell, & Hamilton-Craig, 2017). Eye measures related to workload include blink rate, horizontal gaze dispersion (for highway driving) and pupil diameter (Marquart, Cabrall, & de Winter, 2015).…”

Section: Measuring Workloadmentioning

confidence: 99%

Automated driving reduces perceived workload, but monitoring causes higher cognitive load than manual driving

Stapel

Mullakkal-Babu

Happee

2019

Transportation Research Part F: Traffic Psychology and Behaviou

110

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Driver mental workload is an important factor in the operational safety of automated driving. In this study, workload was evaluated subjectively (NASA R-TLX) and objectively (auditory detection-response task) on Dutch public highways ($150 km) comparing manual and supervised automated driving in a Tesla Model S with moderators automation experience and traffic complexity. Participants (N = 16) were either automation-inexperienced drivers or automation-experienced Tesla owners. Complexity ranged from an engaging environment with a road geometry stimulating continuous traffic interaction, and a monotonic environment with lower traffic density and a simple road geometry. Perceived and objective workload increased with traffic complexity. When using the automation, automationexperienced drivers perceived a lower workload, while automation-inexperienced drivers perceived their workload to be similar to manual driving. However, the detection-response task indicated an increase in cognitive load with automation, in particular in complex traffic. This indicates that drivers underestimate the actual task load of attentive monitoring. The findings also highlight the relevance of using system-experienced participants and the importance of incorporating both objective and subjective measures when examining workload.

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“…Several studies have reported the importance of artefact correction on the quantification of HRV derived parameters from short-term recordings [8,28,29]. However, there is scarce evidence regarding the impact of using different Kubios filters on the quantification of HRV derived parameters from short-term recordings in time-and frequency-domains employing the commercially available Kubios software [10].…”

Section: Discussionmentioning

confidence: 99%

“…HRV recordings using heart rate monitors are affected by technical (e.g., wrong placement of the heart rate monitor's band) and/or biological (e.g., ectopic beats) artefacts. These artefacts could contaminate the HRV recordings, making it difficult to obtain HRV derived parameters from long-term (≈24 h) and especially short-term (≈5 min) recordings [1,7,8]. Artefacts could modify and produce important over-or under-estimation of HRV derived parameters (up to 50%) [9].…”

Section: Introductionmentioning

confidence: 99%

Impact of Using Different Levels of Threshold-Based Artefact Correction on the Quantification of Heart Rate Variability in Three Independent Human Cohorts

Alcantara

Plaza‐Florido

Amaro‐Gahete

et al. 2020

JCM

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Heart rate variability (HRV) is a non-invasive indicator of autonomic nervous system function. HRV recordings show artefacts due to technical and/or biological issues. The Kubios software is one of the most used software to process HRV recordings, offering different levels of threshold-based artefact correction (i.e., Kubios filters). The aim of the study was to analyze the impact of different Kubios filters on the quantification of HRV derived parameters from short-term recordings in three independent human cohorts. A total of 312 participants were included: 107 children with overweight/obesity (10.0 ± 1.1 years, 58% men), 132 young adults (22.2 ± 2.2 years, 33% men) and 73 middle-aged adults (53.6 ± 5.2 years, 48% men). HRV was assessed using a heart rate monitor during 10–15 min, and the Kubios software was used for HRV data processing using all the Kubios filters available (i.e., 6). Repeated-measures analysis of variance indicated significant differences in HRV derived parameters in the time-domain (all p < 0.001) across the Kubios filters in all cohorts, moreover similar results were observed in the frequency-domain. When comparing two extreme Kubios filters, these statistical differences could be clinically relevant, e.g. more than 10 ms in the standard deviation of all normal R-R intervals (SDNN). In conclusion, the results of the present study suggest that the application of different Kubios filters had a significant impact on HRV derived parameters obtained from short-term recordings in both time and frequency-domains.

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The sensitivity of 38 heart rate variability measures to the addition of artifact in human and artificial 24‐hr cardiac recordings

Cited by 31 publications

References 66 publications

Stochastic vagus nerve stimulation affects acute heart rate dynamics in rats

Stochastic vagus nerve stimulation affects acute heart rate dynamics in rats

Automated driving reduces perceived workload, but monitoring causes higher cognitive load than manual driving

Impact of Using Different Levels of Threshold-Based Artefact Correction on the Quantification of Heart Rate Variability in Three Independent Human Cohorts

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