It’s hard to be motivated for a low intensity base-building turbo session. Here’s a challenge to add some interest and focus…
Pick a day between now and next Sunday for a turbo/spin session; with the temp still ~0 it’s a good time for it. Set a personal target HR. For a Z2 effort I’d suggest 85% of your current LTHR (I can give you my estimate of your current LTHR). Do an hour on the turbo and try to stick to the target HR. When you’re done let me know and I’ll analyse your ride. The aim is to get the tightest HR distribution around your target level. In the calculation, I’ll discard the first 10 minutes of the hour so you can set your Garmin going straight away.
Visually, you’re looking for the histogram, which will look something like this, to get as narrow as possible:
Top tip: Although this isn’t a power challenge, using a power meter will cause your Garmin to sample more frequently so you’ll get a more sensitive, less blocky HR reading.
Keen athletes like to train hard, and frequent exercise is great for your health. However, it is necessary to balance training with recovery, and the harder the training the more recovery is needed. Recovery gives our bodies time to adapt to training and thus to become stronger and fitter. For endurance exercise, recovery also works for the heart. There is increasing evidence (see The Haywire Heart box) that endurance athletes are prone to arrhythmias that may be incapacitating. Building recovery into your training regime is a sensible precaution to reduce such risks.
Through this website we provide tools to measure the cardiac stress from exercise in a consistent way. One aspect of this analysis is the systematic analysis of heart rate spikes. This attempts to screen out known failings in popular heart rate monitors that often cause incorrect high heart rate values. Conversely, the analysis also aims to flag spikes that may provide an early indication of potential atrial fibrillation.
Another tool that we use is the Cardiac Stress Score (CSS). Unlike all other such measures of which we are aware, CSS:
accounts for spikes and other anomalies in the heart rate data;
does not depend upon user input values – such as maximum heart rate, Lactate Threshold Heart Rate and Functional Power Threshold – that rely upon measurement protocols and change over time. Instead, we estimate these values from your Strava data;
is directly comparable across activities, exercise types and athletes. This enables you and your Strava training partners to compare your efforts;
can – for cyclists using a power meter as well as a heart rate monitor – be used to track fitness from the relationship of patterns in heart rate and power data.
At the time of writing, this analysis has been calibrated on a year’s worth of activity from a group of 14 keen athletes, all of whom cycle.
Content and tools will be added to the website over the coming months.