I have been collecting data on my Heart Rate Variability (HRV) to determine how to improve my personal performance and reduce stress. In doing so I have come to doubt the usefulness of “stress measurements” touted by some wearable devices and apps. They claim to be able to measure your physiology and indicate when you are stressed. My experience has been that the readings and the physiology is much more complex than a simple “red, amber, green” meter can indicate. It came to a head recently when I had a nicely engaged conversation with a colleague and my physiology readings indicated signs of stress. In fact, the experience had not been stressful at all. We were working hard on solving a problem and I felt engaged.
So I wanted to get a baseline by looking at data where I knew there was no stress at all. I had an HRV reading from an eight minute meditation session where I was completely relaxed and had nothing to distract me. The graph below shows how my heart rate stayed in the range from sixty-four to seventy-four beats per minute, a normal relaxed range for me.
The heart rate is negatively correlated to HRV, meaning that the body when in a state of arousal or stress will elevate the heart rate and naturally lower the amount of variability between beats. The variability in heart rate is examined by looking at the intervals between beats. Here is a graphic showing the “R-R Intervals” and how they vary. You can see in this example how the heart speeds up and slows down beat by beat.
For the eight minute session my RR interval steadily rose and fell. In this graphic I display the distance between beats for the entire period. You can see the distance increase and decrease regularly.
What you see here is my heart rate following my inhalations and exhalations. When we breathe in our heart accelerates and variability decreases. When we breathe out our heart decelerates and variability increases. During this exercise I used a breath pacer set for one breath every ten seconds. This graphic shows one ten second interval where I took one full breath in and out. You can see how the intervals drop on inhalation, rise on exhalation.
When all of the interval changes are put side by side you can see that in a stress free state the changes are regular. The following graph shows the changes both positive and negative in the differences in intervals during the entire eight minute session. Notice that on the outward breath, when the variability is positive, that the scale of the changes are larger than on the inward breath when the variability is negative.This means that the breathing outward has a powerful effect on the overall measured averages of HRV readings.
The averages of the readings, expressed best in the time based measure rMSSD, show for this session a settling at at rMSSD of 55 which is relaxed as any average reading for me indicates no stress when above 48.
But this reading does not give a good picture of what is actually happening physiologically. It looks like in a relaxed state the rMSSD stays above 48 and implies that if I drop below 48 I will be stressed. So a natural reaction would be to try and devise methods that would keep the rMSSD above 48. But this is an average and obscures how variable the underlying heart beats are.
Looking at those successive heart beats where the interval change is “close” or under 25 milliseconds. These beats would indicate a stress response for a lot of the session, but we know this period was stress free. In this graph you see the blue lines are those intervals under 25 milliseconds, and the white spaces are those intervals over 25.
My conclusion is this. In the drive to make wearable devices and apps more palatable to a mass audience the natural tendency is to bring the simplest interface to indicate stress or relaxation, be it a color or a score. This is useful for directing relaxation activity for beginners, and as the quantified self enthusiast digs into the underlying data much more nuanced picture emerges. What the last graph shows is the in the most relaxed and meditative state possible my beat to beat “score” was low for 41% of the beats. The fact is that these low score beats are part of healthy variability that goes both high and low. It isn’t right to see it as “59% good and 41% bad” – it more correct to understand the mix of highs and lows, short term variability and the incredible speed with which the body becomes aroused and can calm itself. Sadly, the Apple Watch will not solve your stress problem. Data collection, repeated measurements and comparison with experience is the only way forward.