What harlen reads, in plain language. Each entry links to the source paper or population norm where applicable.
Recovery debt
The gap between training stress and recovery the body has been given.
Recovery debt shows up when HRV trends down, resting heart rate trends up, and sleep quality slips — but training load held steady. The body is being asked to absorb stress it isn't getting the time to absorb.
Different from overtraining, which is a clinical state that takes weeks to dig out of. Recovery debt is reversible with a handful of easier sessions and two solid nights of sleep. Catching it early is the whole point.
HRV (heart rate variability)
The variation in time between consecutive heartbeats.
Higher HRV usually means stronger parasympathetic recovery; lower HRV signals the body is under load — training, illness, stress, poor sleep. Most consumer wearables measure it overnight.
Read it as a trend against the athlete's own rolling baseline, not as a raw number. A 42 ms morning for an athlete who averages 68 ms means something different than 42 ms for an athlete who averages 45 ms.
Population norms: Nunan et al., 2010 — "A quantitative systematic review of normal values for short-term heart rate variability in healthy adults."
Resting heart rate baseline
The athlete's typical morning RHR after a normal night's sleep.
An elevation of 5–10 bpm above baseline that holds for two or three days correlates with under-recovery, illness onset, or accumulated life stress. One elevated morning is noise; a sustained shift is signal.
Source: Quer et al., 2020 — "Inter- and intraindividual variability in daily resting heart rate."
Training load (acute / chronic)
Two rolling measures of how much training stress the athlete has absorbed.
Acute load is roughly the last 7 days of training stress. Chronic load is roughly the last 28 days. The ratio (acute : chronic) is a coarse zone indicator — above ~1.5 is a spike worth watching, below ~0.8 is a detraining zone.
Useful for catching sudden volume jumps and long stretches of under-training. Not a replacement for reading the athlete in front of you.
Training monotony
The sameness of training across a week.
Same volume every day, same intensity, same days off. Foster (1998) flagged monotony as a stronger predictor of staleness and illness than total load — it's the variation, not the volume, that drives adaptation.
Easy days are part of the program, not breaks from it.
Readiness
A rolled-up estimate of whether an athlete is ready to train hard today.
Typically combines HRV, resting heart rate, sleep, and self-reported inputs (soreness, mood, motivation). Useful as a daily check; bad as a sole decision-maker.
Most wearable apps publish a single readiness number. The underlying inputs matter more than the score — a 72 with crashing HRV reads differently than a 72 with steady HRV and short sleep.
Changepoint detection
A statistical method for finding moments when a time-series genuinely shifts.
Looks at a continuous signal — HRV, resting heart rate, sleep efficiency, training load — and identifies points where the level changed, not just bounced. Small day-to-day noise doesn't trigger anything.
harlen uses PELT (Pruned Exact Linear Time), a published algorithm from Killick, Fearnhead & Eckley, 2012. It's how the platform decides what's worth flagging on a Monday brief and what's normal variance.
VO₂ max
The maximum rate at which the body can use oxygen during exercise.
Measured in ml/kg/min. The single best aerobic fitness number — strongly tied to endurance performance and long-term health.
Lab measurement (treadmill or bike test with gas exchange) is the gold standard. Consumer wearable estimates from Garmin, Apple, and Coros are decent for trend tracking and order-of-magnitude reads, less reliable for absolute values.
Reference: FRIEND registry (Kaminsky et al., American Heart Association).
