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HRV Watch

Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats

Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats

HRV Watch

by Bernhard Hering
HRV Watch
HRV Watch
Apple Watch
HRV Watch Apple Watch App
HRV Watch Offers Apple Watch App
Check the details on WatchAware

What is it about?

Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.

HRV Watch

App Details

Version
1.3
Rating
(8)
Size
22Mb
Genre
Health & Fitness Medical
Last updated
October 1, 2022
Release date
May 1, 2018
More info

App Store Description

Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.
This HRV app provides a way to analyze the HRV SDNN values recorded by the Apple Watch.

Heart rate variability describes the ability of an organism to change the frequency of the heart rhythm. A healthy person constantly adapts the heart rhythm to the current requirements. The number of heart beats per minute is therefore constantly changing, which is a good sign of the organism's ability to adapt.

Researchers at the University of Zaragoza in Spain have shown that the values recorded by the Apple Watch during a session with the Breath app are very accurate. Comparable with professional chest straps.

To filter your own HRV data, this app offers the possibility to display only those HRV values that are recorded during such a session.

The Apple Watch is measuring your HRV Data and writes it to Healthkit.
This app connects with Apple’s Health app to displays the recorded data on a Watch App, a complication and your Iphone.

How to Use:
- ATTENTION: This app only works if you have an Apple Watch Series 3 or later.
- If you want to measure a new value, use the Breath App from Apple.
- To get to most out of your data it is important that you measurement does always take place in the very same situation. For example: "First thing in the morning" before getting up.

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