@Everyday_Normal_Guy , I still seem to have the issue I mentioned above. It’s hit-and-miss if I can export the data after a measurement. In which case I need to close the app. re-open and then I can export.
Hello,
can someone help me!
I get this message and don’t know where and how I can see the data from HRV4 Training.
Thanks !!
Hi all,
I guess I had forgotten about the Dropbox functionality, so I created an R script that will merge data from the HRV4Training export into the Intervals.icu wellness export which can then be re-uploaded. The mapping is as follows.
- HRV4Training Recovery Points → Intervals.icu Readiness
- HRV4Training Training Motivation → Intervals.icu Motivation
- HRV4Training Sleep Time → Intervals.icu Sleep Time
- HRV4Training Sleep Quality → Intervals.icu Sleep Quality
- HRV4Training Mental Energy → Intervals.icu Mood
- HRV4Training Muscle Soreness → Intervals.icu Soreness
- HRV4Training Fatigue → Intervals.icu Fatigue
- HRV4Training Current Lifestyle → Intervals.icu Stress
- HRV4Training Physical Condition → Intervals.icu Sickness
Some of the scales are reversed – either because the metrics are inversely related or because Intervals reversed the order (1-4). The HRV4Training fields also have to be converted as they are scored 1-10 and Intervals.icu uses 1-4.
I have the code set up so it only replaces empty values in the wellness file with HRV4Training data. Like many, I use HealthFit to upload a lot of metrics, and in some cases this data is superior, i.e., HRV4Training’s sleep data doesn’t include naps.
There is a “last_upload” variable at the beginning of the script that will allow you to limit how much data you send back up to Intervals. Of course, you would need to run the R script in a directory with the two csv’s (wellness.csv and hrv.csv). I’d recommend starting with recent dates to make sure it’s working for you. I just uploaded several years and it appears to have worked.
Please let me know if you find any errors. Thanks!
library(tidyverse)
library(janitor)
library(lubridate)
last_upload <- date("2025-03-23")
wellness <- read_csv("wellness.csv")
hrv <- read_csv("hrv.csv")
hrv <- hrv %>% mutate(
new_date = date(date)
) %>% select(
new_date,
sleep_time,
HR_lying,
rMSSD_lying,
HRV4T_Recovery_Points,
sleep_quality,
mental_energy,
trainingMotivation,
current_lifestyle,
physical_condition,
muscle_soreness,
fatigue,
)
translate <- function(col) {
col <- as.numeric(col)
}
scaled <- function(col) {
col = case_when(
col <= 2.5 ~ 1,
col > 2.5 & col <= 5 ~ 2,
col > 5 & col <= 7.5 ~ 3,
col > 7.5 & col <= 10 ~ 4,
.default = NA
)
}
rev_scaled <- function(col) {
col = case_when(
col <= 2.5 ~ 4,
col > 2.5 & col <= 5 ~ 3,
col > 5 & col <= 7.5 ~ 2,
col > 7.5 & col <= 10 ~ 1,
.default = NA
)
}
hrv[3:12] <- lapply(hrv[3:12],translate)
hrv[11:12] <- lapply(hrv[11:12],scaled)
hrv[6:10] <- lapply(hrv[6:10],rev_scaled)
hrv$sleep_time <- as.numeric(hms(hrv$sleep_time))
hrv$sleep_time[hrv$sleep_time == 0] <- NA
hrv$sleep_time[hrv$sleep_time > 50400] <- NA
wellness$restingHR[is.na(wellness$restingHR)] <- round(as.numeric(hrv$HR_lying[match(wellness$date, hrv$new_date)]),0)
wellness$hrv[is.na(wellness$hrv)] <- hrv$rMSSD_lying[match(wellness$date, hrv$new_date)]
wellness$readiness[is.na(wellness$readiness)] <- hrv$HRV4T_Recovery_Points[match(wellness$date, hrv$new_date)]
wellness$motivation[is.na(wellness$motivation)] <- hrv$trainingMotivation[match(wellness$date, hrv$new_date)]
wellness$sleepSecs[is.na(wellness$sleepSecs)] <- hrv$sleep_time[match(wellness$date, hrv$new_date)]
wellness$sleepQuality[is.na(wellness$sleepQuality)] <- hrv$sleep_quality[match(wellness$date, hrv$new_date)]
wellness$mood[is.na(wellness$mood)] <- hrv$mental_energy[match(wellness$date, hrv$new_date)]
wellness$soreness[is.na(wellness$soreness)] <- hrv$muscle_soreness[match(wellness$date, hrv$new_date)]
wellness$fatigue[is.na(wellness$fatigue)] <- hrv$fatigue[match(wellness$date, hrv$new_date)]
wellness$stress[is.na(wellness$stress)] <- hrv$current_lifestyle[match(wellness$date, hrv$new_date)]
wellness$Sickness[is.na(wellness$Sickness)] <- hrv$physical_condition[match(wellness$date, hrv$new_date)]
wellness <- wellness %>% filter(
date >= last_upload & date < now()
)
write_csv(wellness,"for_intervals.csv",na="")
1 Like
Yeah, I thought they fixed it but alas no.
also, Marco never replied to me.
It works for me, when i close the app, reopen it and go straight to the export to dropbox feature