Category: HRV Observations

In the Good Friday edition we’re going to explore another of my favourite pastimes Mountain Biking (MTB) and its’ impact on Heart Rate Variability (HRV). Why I hear you ask? well because my “mobile office” is fitted with a FatigueM8 unit and is collecting every time I drive, we’ve observed patterns in my HRV after exercising, so let’s take a look.

In early 2020, escaping the smokey conditions in the Nation’s Capital for a day my mates and I headed for Thredbo for a day of MTB’ing fun.

With my mobile office loaded to the roof, we left Canberra at 5:30am.  Making our way down the Monaro Highway, we avoided all of the wildlife on the sides of the road and made it incident free. Our day at Thredbo was epic, covering 85kms, 10 runs down the mountain and  8 hours of activity.

Starting the drive home I was physically tried, but not in a sleepy sense, still on a high from all of the days action. We made it home incident free and safely into bed for a well earned shut eye.

The following afternoon, as is the case after most trips in my car, I started to review the data collected, correlating how I was feeling, the road conditions and any other points of interest. When reviewing the data collected by the FatigueM8 on return that I noticed an interesting pattern in my HRV on this trip.

The trip from Canberra to Thredbo was similar to the other early morning starts, my HR was steady hovering between ~60-65 beats per minute (BPM). The Heart Rate Variation (HRV) was also as expected after having had a solid nights sleep before before starting the journey. The graph (above) show’s the morning’s journey, the blue plot the RR Interval (time between beats), with the black line plotting the moving average (based on the last 20 samples). The red line plots the Heart Rate (HR). Everything was pretty much as expected and similar to my other early morning trips.

Looking at the observations from the return trip, the graph below, it’s clear to see the difference in the HRV pattern.

The return trip is characterised by minimal HRV variance, as can be seen by the relative flat lines of black, blue lines. My heart rate at the beginning of the trip (the left of the graph) was elevated ~ 90 BPM and then reduced through the course of the return trip ~70-75 BPM. Interestingly, the HR didn’t drop back to the resting rate observed on the morning trip, finishing the trip (on the right of the graph) around 80 BPM.

Before reviewing the data, I had expected to see similar patterns to the return trips from Sydney to Canberra, and when it didn’t present in that manner I began to research what the cause was likely to be. Fortunately I came across a paper “Cardiac Autonomic Responses during and Post-exercise Recovery Using Heart Rate Variability and Systolic Time Intervals – A Review 2017” by Michael et al. which was able to provide an explanation to the HRV pattern being presented in the data.

The of Michael et al’s review was to “to summarise: (a) summarise relevant literature relating to cardiac autonomic control during exercise and recovery; (b) present relevant background information on the measurement and interpretation of HRV; (c) examine and summarise the existing literature regarding how key exercise does factors (intensity, duration and modality) influence HRV responses to dynamic “aerobic” exercise, in particular during post-exercise recovery; (d) examine and summarise the existing literature regarding STI responses to exercise and recovery.”

In the paper they explain that HRV is reduced during exercise, as the body responds to the exercise demands, driven largely by the Sympathetic Nervous System (SNS). The SNS controls the bodies “fight or flight” state, ensuring that the HR increases blood flow to the bodies vital organs and muscles, as well as many other physiological responses. After the exercise challenge subsides, “both HR and HRV demonstrate a time-dependent recovery and eventual return to pre-exercise levels” found Stanley et al. 2013. Stanely et al  also found that “a higher exercise intensity is associated with a slower recovery of the Parasympathetic Nervous System (PNA)” which was definitely the case post Thedbo, with my HRV and HR taking somewhere between 4 and 12 hours to recover.

In the diagram below is both the whole CBR-Thredbo-CBR trip, plus the next mornings’ data, which shows an elevated HR (~70-75 BPM). Whilst the HRV is greater than the drive home, but still not back to the pre-exercise levels (where the green arrow is).

Based on our earlier observations, there a similar HRV characteristics when comparing the effective of intense exercise and signs of fatigue; both show a reduction of HRV and an increased HR.

The other interesting point to note, is the effect that the intense exercise the previous day had on the HR & HRV characteristics the next morning. At the core of our FatigueM8 solution is a personalised alerting system and as we collect more and more data from different drivers, under difference conditions we’re better able to predict and  identify the state of the driver.

Until next week, stay safe.

Paper reference: doi: 10.3389/fphys.2017.00301

It’s FatigueM8 Friday and to kick off, here’s the photo of the week – sunrise over the Elvin yard this morning.

This week I’m focusing on the heart rate variability;  with COVID-19 grabbing a majority of the headlines, there was a couple of articles that got my attention (links at the bottom of this post). There has been a couple of articles published looking at the use of changes in Heart Rate (HR) as an early indicator of a person’s immune system starting to fight an infection. In our observations of heart rate variability (HRV), we’ve seen examples of in baseline HR and HRV as a result of different physiological events and immune responses (not COVID-19 related).

This week we’ll look at two (2) trips too and from Sydney. The first trip we’ll use as the baseline (shown below), we looked at this trip previously with a fatigue lens.

During Trip 1 there was periods of high HRV (Blue & Black lines) and periods with lower HRV (middle of the graph), correlating to increased fatigue being experienced by the driver (which was me!).

The second trip (show below) to Sydney was completed with similar start times (~5am), with the return trip was in the afternoon as compared with the night time return in Trip 1.

If we focus in on the drive to Sydney in the morning, the HRV and HR (Red lines) are similar (as shown below), starting with lower HRV and as the drive progresses the HRV increases. We think this is likely to be connected to the Circadian Rhythm, which we’ll explore in another post. The HR remained pretty constant until right at the end of the trips, which corresponds to hitting North Sydney and having to navigate traffic and find a car park (stressful times for a Canberra driver in the big smoke).

The return drive from Sydney back to Canberra is where we observe some differences in the HRV and HR. It’s import to note the in Trip 1 the driving began at 5:30pm, whereas Trip 2 the driving began at 2:45pm.

We observed in Trip 2 that the HRV and HR is much narrower than was observed in Trip 1. It just so happened on this trip that the driver (me again) suffered a “bout of gout” on the day. I could feel the attack coming on in the morning, just as a tingle, but as the day progressed the attack got worse. The most visible effect of gout (in my case) is a swelling of the big toe on my right foot (which is kind of important when driving). With the swelling comes acute pain and reduced flexibility. The impact on HRV and HR is quite evident when comparing the two Trip’s graphs. What we can see is a sustained period of reduced HRV, combined with an elevated HR, which is the bodies immune response to fighting the Bout of Gout.

Interestingly, in our FatigueM8 trials we’ve observed a similar pattern in response to intense exercise, which we’ll cover this off in the next FatigueM8 Friday!

Stay safe until next Friday.

https://helpwithcovid.com/projects/351-crowdsourcing-resting-heart-rate-to-predict-covid-19-spread

https://www.alivecor.com/press/press_release/new-fda-guidance-allows-use-of-kardiamobile-6l-to-measure-qtc-in-covid-19-patients/

FatigueM8 Friday’s (post 2).

We’ll kick off with the photo of the week (as judged by me!). The front facing camera has captured some stunning sunrise photos, enhanced somewhat by the lack of an Infrared filter #nofilter literally! This one was from Friday morning just before 5:55am.

This week saw the FatigueM8 journey take another leap forward with the deployment of a site-collection point (wifi + 4G). Also known as the FatigueM8 comm’s box.

The Comm’s box implementation is simple, but effective, and allows for all the FatigueM8 units to transmit data whenever they’re in the yard. The work patterns of the cement trucks aka as “Agi’s” pronounced “ad-geez”, is they get filled with concrete/cement in the yard, then deliver the load to site, before returning to the yard. The timing of the trips is anywhere from 30 mins to several hours and this lends itself well to periodic upload and analysis by FatigueM8.

The Comm’s box, when combined with the persistently installed FatigueM8 unit allows for constant collection and analysis of the drivers ECG activity during the day.

Now with the data following in from our drivers, we’ve created a simple dashboard using AWS Quicksight, drawing data from S3 via Athena. Currently the dashboard compares the statistic’s of two (2) of our drivers. We compare the number of valid ECG readings, average heart rate by hour of the day, Root Mean Square of Successive Differences (RMSSD) and a plot of the journeys the drivers have taken via GPS recordings. The RMSSD is one of the time domain measurements that can be used to Heart Rate Variance (HRV). These graphs have a weeks worth of aggregated for display.

This week, one of the GPS’s had an issue and hence the reason there is only one colour (blue) on the map plot.

An interesting point to note about driver 2019-0001, who’s data is represented in blue across all of the graphs, is the gap from in the data consistently between 9am and 10am. This gap corresponds to their attendance in the office for a daily COVID-19 meetings.

Until next week, stay safe, socially distanced but not isolated #stayconnected.