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Attention Score in Context
| Title |
Influence of Heart Rate in Non-linear HRV Indices as a Sampling Rate Effect Evaluated on Supine and Standing
|
|---|---|
| Published in |
Frontiers in Physiology, November 2016
|
| DOI | 10.3389/fphys.2016.00501 |
| Pubmed ID | |
| Authors |
Juan Bolea, Esther Pueyo, Michele Orini, Raquel Bailón |
| Abstract |
The purpose of this study is to characterize and attenuate the influence of mean heart rate (HR) on nonlinear heart rate variability (HRV) indices (correlation dimension, sample, and approximate entropy) as a consequence of being the HR the intrinsic sampling rate of HRV signal. This influence can notably alter nonlinear HRV indices and lead to biased information regarding autonomic nervous system (ANS) modulation. First, a simulation study was carried out to characterize the dependence of nonlinear HRV indices on HR assuming similar ANS modulation. Second, two HR-correction approaches were proposed: one based on regression formulas and another one based on interpolating RR time series. Finally, standard and HR-corrected HRV indices were studied in a body position change database. The simulation study showed the HR-dependence of non-linear indices as a sampling rate effect, as well as the ability of the proposed HR-corrections to attenuate mean HR influence. Analysis in a body position changes database shows that correlation dimension was reduced around 21% in median values in standing with respect to supine position (p < 0.05), concomitant with a 28% increase in mean HR (p < 0.05). After HR-correction, correlation dimension decreased around 18% in standing with respect to supine position, being the decrease still significant. Sample and approximate entropy showed similar trends. HR-corrected nonlinear HRV indices could represent an improvement in their applicability as markers of ANS modulation when mean HR changes. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 20% |
| Student > Ph. D. Student | 9 | 20% |
| Student > Doctoral Student | 4 | 9% |
| Professor > Associate Professor | 4 | 9% |
| Student > Master | 3 | 7% |
| Other | 7 | 16% |
| Unknown | 9 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 10 | 22% |
| Medicine and Dentistry | 9 | 20% |
| Neuroscience | 3 | 7% |
| Sports and Recreations | 3 | 7% |
| Agricultural and Biological Sciences | 2 | 4% |
| Other | 5 | 11% |
| Unknown | 13 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 November 2016.
All research outputs
#18,482,034
of 22,901,818 outputs
Outputs from Frontiers in Physiology
#8,175
of 13,693 outputs
Outputs of similar age
#232,255
of 306,450 outputs
Outputs of similar age from Frontiers in Physiology
#124
of 197 outputs
Altmetric has tracked 22,901,818 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,693 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 306,450 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 197 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.