Garmin FIT files for RHRV analysis

2. csv to beats files for RHRV analysis

** 2.1. Load readr package to read/write csv, Excel files.**

Code

if(!require("readr", quietly = TRUE)){
  install.packages("readr");require("readr")
}

2.1.1. Read the csv file created in the previous part.
*Note: Enter the file number to be processed in FileNo<-xx.
Pre-process data files so that they can be processed by RHRV.

Code

FileNo <- 1
FileName <- paste0("time_HR_", FileNo, ".csv")

data <- read.table(file.path("csv_xls", FileName), header = TRUE, sep = ",", colClasses = c("character", "numeric"))

hr <- data[,2]
rr <- 1/hr
rr = rr*60*1000

2.1.3. Load the package RHRV.

Code

if(!require("RHRV", quietly = TRUE)){ install.packages("RHRV");require("RHRV") } 

library(RHRV)

2.1.4. Create a data frame for RHRV analysis.

To compute the HRV time series the BuidNIHR function is used (Build Non Interpolated Heart Reate).
This function constructs both the RR (Equation 2.1) and instantaneous heart rate (HR) series (Equation 2.2) described in Section 2.1*.  *Getting started with RHRV version 2.0.

RR{n}=a(t_{n}-t_{n-1})~~~~~~~~~~(2.1)~~~~~~~~~~　　 HR{n}=\frac{β}{t_{n}-t_{n-1}}~~~~~~~~~~(2.2)

Code

hrv.data <- CreateHRVData()
hrv.data <- SetVerbose(hrv.data, TRUE)
hrv.data$Beat$RR = rr
hrv.data$Beat$niHR = hr
hrv.data$Beat$Time = cumsum(rr)/1000

2.1.5. Create a data frame for RHRV analysis.

Figure 1: Plot of the episodic information

Code

hrv.data <- FilterNIHR(hrv.data)
PlotNIHR(hrv.data)
hrv.data <- InterpolateNIHR(hrv.data, freqhr = 4)
PlotHR(hrv.data) 

(a) Non-interpolted Heart Rate time plot

(b) Interpolted Heart Rate time plot

Figure 1: Heart Rate time plot (Marathon 2023/11/29)

2.1.6. Create a data frame for RHRV analysis.

Code

hrv.data <- CreateTimeAnalysis(hrv.data, size = 300, interval = 7.8125)

Code

library(tidyverse)

df <- hrv.data$TimeAnalysis %>%
    as.data.frame() %>%
    slice(1, 2) %>%
    select(2:11)

Code

# Table 1: Summary of the previous pages
knitr::kable(df[1:10], caption = "Table 1: Summary of the analysis", digits = 3, booktabs = TRUE)

Table 1: Summary of the analysis

SDNN	SDANN	SDNNIDX	pNN50	SDSD	rMSSD	IRRR	MADRR	TINN	HRVi
19.234	15.853	8.287	0	1.717	1.717	21.533	0	51.92	3.323