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| RE: Method to identify VT1 and VT2 via HRV analysis [ Reply ] By: Abraham Otero on 2017-01-25 12:34 | [forum:43825] |
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I am afraid that currently do not have any function to compute those thresholds in RHRV. However, given that you are trying to reproduce the results of somebody else paper, I suggest you read this: https://www.researchgate.net/profile/Arturo_Mendez/publication/45630438_Detecting_Sleep_Apnea_by_Heart_Rate_Variability_Analysis_Assessing_the_Validity_of_Databases_and_Algorithms/links/09e41509cf320c98e8000000.pdf |
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| Method to identify VT1 and VT2 via HRV analysis [ Reply ] By: Laurent Therond on 2017-01-24 00:51 | [forum:43823] graph.png (5) downloads
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I am trying to reproduce the results described in this research paper: https://dl.dropboxusercontent.com/u/29886031/images/graph.png https://dl.dropboxusercontent.com/u/29886031/images/text1.png https://dl.dropboxusercontent.com/u/29886031/images/text2.png RHRV does a great job getting me close. For the last step, I do: HFFHF = unlist(lapply(hrv.data$FreqAnalysis[[1]]$HF, function(x) { x * hrv.data$FreqAnalysis[[1]]$HFmax })) plot(HFFHF, typ="l") I think that's the metric the paper uses, but I am not entirely clear about that. Is there a better way to use RHRV to detect the first HF-HRV threshold (HFT1) and the second ventilatory threshold and the second HF-HRV threshold (HFT2)? |
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