--- title: "RHRT: Synopsis for the hasty (Quick-start guide)" author: "Valeria Blesius" date: "`r Sys.Date()`" output: rmarkdown::html_vignette: keep_md: true vignette: > %\VignetteIndexEntry{RHRT: Quick-start guide} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- The RHRT package helps you assess **Heart Rate Turbulence** (HRT) in RR intervals and calculate **turbulence onset** (TO), **slope** (TS) and **timing** (TT). It can plot the tachograms and checks the results for reliability. The **ventricular premature beats** (VPCs) with **coupling** (CPI) and **compensatory interval** (CMI) can either be given with annotations or found on the basis of the filter rules as first described by [Grimm et al. 2003](https://doi.org/10.1046/j.1542-474X.2003.08206.x). The type of average and order of calculation for all parameters can be set. This vignette sums up the most common functions and parameters needed when using RHRT. -------- ## Loading package and data ```{r} library("RHRT") # testdataLong is a numeric vector of RR intervals in msec data("testdataLong", package = "RHRT") ints <- testdataLong # testdataLong_Ann is a character vector of annotations corresponding to testdataLong data("testdataLong_Ann", package = "RHRT") ann <- testdataLong_Ann ``` ## Checking interval data for HRTs The **core function** of RHRT is `vectorToHRT` that finds valid VPCs in RR intervals and returns an `HRTList` object (see *HRTList object* in [Objects & Functions](objects_functions.md) for more information): ```{r} hrtl <- vectorToHRT(ints) ``` Every RR interval sequence that matches the needed interval lengths is considered to be a coupling and compensatory interval of a VPC, which can lead to wrong matches. If your data is annotated, you can provide the **annotation data** with the parameters `annotations` and `PVCAnn`. ```{r} hrtl <- vectorToHRT(ints, annotations = ann, PVCAnn = "V") ``` Other parameters are: * `numPreRRs` & `numPostRRs` are used to modify the **filter rules** to find HRTs (number of intervals before and after the VPC that have to match the filter criteria). * `minHRT` is the **minimal number of HRTs** needed to calculate HRT / create a HRTList * `normHallstrom` defines whether TS should be **normalised** with the method of Hallstrom et al. (see the chapter *Normalisation of Turbulence Slope* in the [scientific background](background.md) for more information). ## Getting HRT parameters or class ```{r} getResults(hrtl) # get the HRT class of the data ``` Per default `getResults` checks whether all needed HRT parameters can be calculated reliably. This is done via a t-test per parameter value (for more information see chapter *Reliability Check* in the [scientific background](background.md) vignette). If any of the parameter values is **not reliable** `getResults` returns NR (not reliable). ```{r} getResults(hrtl, safe = FALSE) # get the HRT class without safety check ``` In addition to the classification system HRT0-2 RHRT implements **HRTA-C** that is based on the three parameters TO, TS and TT. ```{r} getResults(hrtl, safe = FALSE, TT = TRUE) # include TT ``` With the parameter `type` you can choose between getting only the HRT **class**, all **parameter values** or the parameter values with the corresponding **p-values** (types "class", "parameter" or "full", respectively). ```{r} getResults(hrtl, type = "parameter", TT = TRUE) # get the averaged HRT parameters ``` Other parameters are: * `nTS`: the **normalised TS** is returned or used for classification instead of TS. * `num`: forces the function to return **numerics** when using `type = parameter`. Depending on the results and your setting of `type` the `getResults` returns characters or numerics. * `pmax`: changes the needed **significance level** for the parameters to be reliable. ## Plotting ```{r, fig.width=7, fig.height=4} plot(hrtl, TT = TRUE) # plots the averaged VPCS and all underlying VPCSs in background ``` Per default the VPCS is **zoomed** in. If you want to also see the CPI and CMI use `cropped = FALSE`. ```{r, fig.width=7, fig.height=4} plot(hrtl, cropped = FALSE) # shows also coupling and compensatory interval ``` -------- Further information can be found in the other vignettes about the [objects and functions](objects_functions.md), the [scientific background](background.md) or with [example pipelines](examples.md).