Introduction: I’m pretty fortunate in the teaching I do at Southern
Cross University, as it’s all focused on the Master of Clinical Exercise
Physiology. One of the units I teach is ‘cardiovascular health’, for
which students must learn to conduct clinical graded exercise tests
– an important component of which is preparation and monitoring of
a 12-lead electrocardiogram (ECG).
Now, not only is stress testing and ECG my area of clinical
expertise, but I’ve also got state of the art wireless 12-lead ECGs to
teach the students on and use in our student-led clinics. As a fitness
professional, you’ve probably known someone who has undergone a
stress test or had a resting ECG.
For our students, it’s critically important that they are able
to recognise a number of heart arrhythmias, and that they can
properly identify these arrhythmias at rest (as this may preclude
the patient from even attempting to complete the stress test) and
during exercise and recovery (to ensure there are no arrhythmias that
develop during exercise or post-exercise, particularly life threatening
arrhythmias, and that no changes occur on the ECG which are
indicative of cardiovascular disease). The students must also ensure
the haemodynamic (heart rate and blood pressure) responses are
normal pre, during and post stress test.
We must note that it is an absolute requirement that stress tests
(submaximal or maximal) are conducted with ECG monitoring to
help ensure the safety of each patient. And hence, ECG monitoring is
considered the gold standard. Imagine if you could offer your clients
that level of monitoring when they are exercising... if only! And this
takes us into this Research Review, where Dr Thompson and her
colleagues investigated the accuracy of assessing heart rate during
exercise using wearable physical activity monitors.
Now, Dr Walsh and I are once again delving into the holy grail
of publications, as our 2016 Research Review (Wrist-worn tech:
investment or waste of money?) stimulated a huge response
(understandable, as a number of our readers found out that their
costly device was inaccurate, ouch!). So please, remember that we
are only providing factual findings from a published, peer-reviewed
scientific study. Let us reiterate again in this Research Review, our
12-lead wireless ECGs cost in excess of $14,000 each, whereas
consumer-orientated wearable devices are considerably less
expensive, i.e. not even 5% of the price! So, to an extent, you do get
what you pay for!
Dr Thomas and her colleagues’ aim was to determine the validity
of exercise heart rate at different intensities for two popular wearable
devices; the Fitbit Charge 2 and the Apple Watch. These devices
were compared to a simultaneous ECG monitoring. The protocol had
participants wearing the Fitbit Charge 2 on their left wrist, the Apple
Watch on their right wrist and a standard 12-lead ECG. Heart rate
readings were taken each minute from each of the devices and ECG
during the entire exercise protocol. The exercise protocol consisted
of subjects completing a maximal exercise test using the Bruce
Protocol treadmill test (Table 1). Heart rate was assessed in the last
10 seconds of every minute on both devices and the 12-lead ECG.
TABLE 1.
Bruce Protocol Treadmill Test
Stage Minutes Speed
(km/h) Grade(%)
1 3 2.7 10
2 6 4.0 12
3 9 5.4 14
4 12 6.7 16
5 15 8.0 18
6 18 8.8 20
7 21 9.6 22
8 24 10.4 24
9 27 11.2 26
Results: The resting heart rates were similar
between genders: males at approximately 70
beats per minute and females slightly lower at
66 beats per minute. The researchers broke
the exercise intensities down relative to each
participant’s heart rate reserve (HRR: age-
predicted heart rate max minus resting heart
rate). Intensity was categorised according
to the American College of Sports Medicine
definitions of very light (<20% HRR), light (20–
40% HRR), moderate (40–60% HRR), vigorous
(60–85% HRR), and very vigorous (>85% HRR).
As this study had a large number of results,
we have chosen here to focus on the ‘Group’
results for each of the intensities, in which the
males’ and females’ data was combined into
one group.
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