Garmin watches measure stress by tracking heart rate variability (HRV), the tiny fluctuations in timing between consecutive heartbeats. A proprietary algorithm developed by Firstbeat Analytics converts those beat-to-beat intervals into a stress score on a 0–100 scale, calibrated to your personal baseline.1Biomedical Signal Processing and Control. Measuring stress using wearable devices – Section: 2.3. Device and stress metric The number you see on your wrist is not measuring your emotional state directly, though. It is reading shifts in your autonomic nervous system, which makes the score both more useful and more easily misunderstood than most people realize.
Why Heartbeat Timing Reflects Stress
Your heart does not beat like a metronome. Even at rest, the gap between one beat and the next varies slightly, sometimes by tens of milliseconds. That variation is heart rate variability, and it is shaped by the ongoing tug-of-war between two branches of your autonomic nervous system. The sympathetic branch speeds things up when you are alarmed or exerting yourself, while the parasympathetic branch (driven largely by the vagus nerve) slows things down when you are relaxed or recovering. HRV is widely recognized as a non-invasive biomarker of this balance.2PubMed Central. Harnessing non‑invasive vagal neuromodulation: HRV biofeedback and SSP for cardiovascular and autonomic regulation
When the parasympathetic side is dominant, your heart rhythm is more variable because the vagus nerve is actively fine-tuning the pace beat by beat. That higher variability generally signals a calm, recovered state. When the sympathetic side takes over, the heart locks into a more rigid, faster rhythm with less variation. Parasympathetic activity, or “vagal tone,” has been linked to self-regulation across cognitive, emotional, and social domains, which is part of why researchers began treating HRV as a window into stress in the first place.3PubMed Central. Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting
So when Garmin says your stress is high, it is really saying your autonomic nervous system is tilted toward sympathetic dominance, with reduced beat-to-beat variation. When it says you are relaxed, your vagus nerve is actively moderating your heart rhythm, producing more variability. The translation from HRV data to “stress” is a simplification, but it is grounded in decades of cardiovascular physiology.
How a Wrist Sensor Reads Your Heartbeat
Clinical HRV measurement uses an electrocardiogram (ECG), which tracks the electrical activity of the heart with electrodes on the chest. A Garmin watch does not have that luxury. Instead, it uses photoplethysmography, or PPG: green LEDs on the back of the watch shine light into the skin, and a photodetector measures how much light is absorbed. Each time your heart pumps blood into the tiny vessels in your wrist, the absorption changes slightly. The watch identifies the systolic peak in the PPG waveform, which corresponds to the moment blood arrives at the wrist after each heartbeat, and measures the time between consecutive peaks to estimate beat-to-beat intervals.4Biomedical Signal Processing and Control. Machine learning framework for Inter-Beat Interval estimation using wearable Photoplethysmography sensors
This method is inherently less precise than chest-based measurement. In a study comparing several wrist-worn devices against a medical-grade three-lead ECG, the Garmin Vivosmart HR showed a concordance correlation of 0.89, which is a reasonable level of agreement for heart rate but a step below a chest strap monitor, which hit 0.98.5PubMed Central. Accuracy of commercially available heart rate monitors in athletes: a prospective study Heart rate accuracy and HRV accuracy are not the same thing, though. Estimating the average heart rate over 30 seconds is forgiving of small errors; estimating the precise gap between individual beats is not. Any wobble in the signal, from wrist movement, a loose band, or poor skin contact, can introduce noise that looks like genuine HRV variation or masks real variation.
Researchers have flagged this as an inherent challenge: wrist-based PPG signals are easily corrupted by motion artifacts, making accurate beat interval measurement difficult.6Physiological Measurement. Novel heart rate variability index for wrist-worn wearable devices subject to motion artifacts that complicate measurement of the continuous pulse interval Garmin and its competitors use filtering algorithms to compensate, but the physics of the situation mean that your stress reading during a vigorous arm-swinging walk is less trustworthy than the one taken while you are sitting at your desk or lying in bed.
The Firstbeat Algorithm and What the Numbers Mean
Garmin does not simply display a raw HRV number. The stress score you see is generated by a proprietary algorithm from Firstbeat Analytics, a Finnish company Garmin acquired in 2020. The algorithm ingests beat-to-beat interval data and outputs a single number from 0 to 100, where lower values indicate rest and higher values indicate stress. The score is calibrated to your own baseline, meaning the watch learns what “normal” looks like for you over time and flags deviations from that personal norm.1Biomedical Signal Processing and Control. Measuring stress using wearable devices – Section: 2.3. Device and stress metric
Garmin typically breaks the 0–100 range into color-coded zones: rest (blue, roughly 0–25), low stress (orange-ish, roughly 26–50), medium stress (deeper orange, roughly 51–75), and high stress (red-toned, roughly 76–100). The exact thresholds and colors depend on the device model and software version, but the general structure is consistent across the lineup.
Because the algorithm is proprietary, Garmin has not published the full details of how it weights different HRV metrics. Researchers studying HRV typically analyze it in several ways. Time-domain measures look at the statistical spread of beat intervals over a recording period. Frequency-domain measures decompose the signal into component rhythms at different speeds, separating sympathetic and parasympathetic contributions. Non-linear measures assess how unpredictable and complex the rhythm is.7PubMed Central. An Overview of Heart Rate Variability Metrics and Norms Independent testing has found that Garmin’s stress score correlates with several of these metrics, including RMSSD (a common time-domain measure of parasympathetic activity) and the SD2/SD1 ratio (a non-linear measure), as well as with plain heart rate.8PubMed Central. Assessing Stress Level Scores Against Wearables-Driven Physiological Measurements This tells us the algorithm is genuinely drawing on recognized HRV features, not just repackaging heart rate under a fancier label, though heart rate itself clearly plays a role in the final number.
How Well the Stress Score Tracks Real-World Stress
Here is where things get interesting and a little humbling for the technology. When researchers compared Garmin’s stress score against both physiological measurements and participants’ own reports of how stressed they felt, the results were mixed. The score did distinguish between rest and stress conditions in a statistically meaningful way, and it correlated with established HRV markers. But when it came to predicting whether a person actually felt stressed, the Garmin score had only marginal predictive value. In fact, plain heart rate alone was a stronger predictor of self-reported stress than the Garmin algorithm.8PubMed Central. Assessing Stress Level Scores Against Wearables-Driven Physiological Measurements
This gap makes sense once you understand what the score is actually measuring. Your autonomic nervous system responds to physical exertion, digestion, caffeine, alcohol, illness, and ambient temperature, not just psychological worry. A high stress reading after lunch does not mean you are anxious about your afternoon meeting; it may mean your body is diverting blood to your gut. Similarly, a low stress reading does not necessarily mean you are in a zen-like emotional state. It means your autonomic balance happens to be parasympathetically tilted at that moment. The score is a physiological gauge, not a psychological one, and that distinction matters for interpreting it usefully.
Everyday Things That Move Your Stress Score
Alcohol is one of the most reliable stress score inflators. If you have ever noticed your Garmin screaming “high stress” all night after a few drinks, it is not wrong, it just is not telling you what you think. Binge-level alcohol consumption reduces both frequency-domain and time-domain HRV components during sleep, suppressing the parasympathetic tone that normally dominates your cardiovascular system overnight.9SLEEP. Evening binge alcohol consumption disrupts cardiovagal tone and baroreflex function during polysomnographic sleep Your body is genuinely under more cardiovascular strain, so the score is accurate in a physiological sense. It just does not know the stressor is a bottle of wine rather than a looming deadline.
Illness is another major driver. Systemic infections consistently reduce HRV, and the reduction correlates with the severity of the infection.10PubMed Central. Clinical review: a review and analysis of heart rate variability and the diagnosis and prognosis of infection A systematic review found this relationship held across both healthy subjects experiencing inflammation and clinical patient groups dealing with nosocomial infections or sepsis.11PubMed. Heart rate variability as a marker and predictor of inflammation, nosocomial infection, and sepsis – A systematic review Some Garmin users have reported that their stress scores spiked a day or two before they developed symptoms of a respiratory illness, and research supports the idea that this is more than coincidence. In a study of elite female soccer players, HRV dropped significantly both one and two days before a positive COVID-19 test compared to each player’s baseline, suggesting wearable HRV monitoring could function as an early warning system for brewing infections.12PubMed Central. Heart rate variability in female soccer players, before, during, and after a COVID-19 positive test
Physical activity adds another layer of complexity. During exercise, your stress score will naturally spike because your sympathetic nervous system is engaged and HRV drops. Garmin’s algorithm knows this and typically grays out the stress graph during detected activity, but the transition periods before and after exercise can still produce readings that look alarming if you take them at face value. There is also an interesting longer-term effect: regular physical activity appears to improve autonomic recovery. Active commuters, for instance, demonstrated roughly an 8% faster return to baseline HRV after commuting compared with people who commuted passively, though very intense exertion during the commute actually slowed short-term recovery.13PubMed Central. Active Travel Commuting and Autonomic Stress Recovery in Urban Populations
Why Your Baseline Differs From Everyone Else’s
Two people wearing the same Garmin model can have dramatically different stress scores during the same activity, and neither watch is wrong. Age is the single biggest source of individual variation in HRV. Overall autonomic variability, captured by a metric called total power, declines consistently from childhood through old age, with both sympathetic and parasympathetic components falling over time.14PubMed. Effect of age and sex on heart rate variability in healthy subjects A 25-year-old with a “normal” resting HRV will typically have higher variability than a 55-year-old, even if both are equally healthy and calm.
Sex also plays a role, though the pattern is more nuanced. Men tend to show higher values on most HRV time-domain measures across age groups.15PubMed Central. Age and Sex Differences in Heart Rate Variability and Vagal Specific Patterns – Baependi Heart Study That same study found an interesting wrinkle: parasympathetic-associated measures showed a U-shaped curve, declining through middle age and then rising again after about 60, while measures reflecting overall sympathetic-parasympathetic balance declined more linearly. Other research has found that after controlling for body composition and physical activity, men had significantly longer average intervals between heartbeats than women, but differences on other HRV measures were less clear.16PubMed. Impact of age and sex on heart rate variability and cardiometabolic function in healthy adults
Garmin’s personal baseline calibration is meant to address some of this. Because the algorithm learns what is normal for you specifically, a 60-year-old woman and a 25-year-old man are not being judged against the same yardstick. But this calibration takes time, and the first week or two of data from a new device can be erratic as the system builds its model. If you change medications, start a new training program, or go through menopause, the baseline may take a while to catch up.
When the Score Gets It Wrong
Beyond the expected noise from motion and the confounders from diet or illness, there are situations where the stress score can be actively misleading. Certain cardiac conditions produce irregular heartbeats that contaminate HRV measurements. Premature ventricular complexes (PVCs), one of the most common types of irregular heartbeats, significantly alter HRV values. Patients with frequent PVCs show lower overall variability and a shifted balance between sympathetic and parasympathetic frequency bands compared to healthy controls.17PubMed Central. The significance of heart rate variability in patients with frequent premature ventricular complex originating from the ventricular outflow tract The Garmin algorithm has no way to distinguish a PVC-shortened interval from a genuinely variable one, so people with arrhythmias may see stress scores that do not reflect their actual autonomic state at all. If you have a known cardiac rhythm issue, treat the stress feature with skepticism.
Fit and skin tone matter too, though Garmin does not always emphasize this. PPG sensors work by detecting changes in light absorption through the skin, and darker skin tones absorb more of the green light these sensors emit, which can reduce signal quality. A loose or poorly positioned band also introduces gaps in the data. Tattoos on the wrist, particularly dark or densely inked ones, can interfere with the sensor entirely. None of these issues are unique to Garmin; they are inherent to the PPG approach used by virtually all wrist-based wearables.
Medications are another overlooked confounder. Beta-blockers, for instance, directly alter heart rate and HRV by blocking sympathetic stimulation of the heart. Someone on a beta-blocker may show unusually high HRV and artificially low stress scores, not because they are relaxed, but because the drug is masking sympathetic drive. Conversely, stimulant medications for ADHD can push HRV in the other direction. The watch has no knowledge of your medication list.
Making Practical Use of the Data
Given all these caveats, should you even bother looking at the stress score? The answer is yes, as long as you treat it as a trend tracker rather than a diagnostic tool. A single reading at any given moment is a snapshot influenced by what you ate, how much you slept, whether your watch band is snug, and a dozen other factors. But patterns over weeks and months reveal something real about your body’s recovery capacity and overall autonomic load. Early research into consumer wearables for health monitoring suggests they have genuine potential for tracking clinically relevant relationships, such as those between chronic stress and burnout risk, especially when data is analyzed over time rather than in isolated snapshots.18PubMed Central. Toward burnout prevention with Bayesian mixed-effects regression analysis of longitudinal data from wearables: a preliminary study
The most informative data point for most users is the overnight stress reading. Sleep is the closest thing to a controlled measurement environment your watch will encounter: you are still, the band is in consistent contact with your skin, and there is no exercise or meals to muddy the picture. If your overnight stress averages are gradually creeping upward over several weeks without an obvious explanation like illness or a new medication, that pattern is worth paying attention to. It may point to accumulated sleep debt, overtraining, or chronic psychological stress affecting your autonomic recovery.
Comparing yourself to other people’s scores is mostly pointless, given the individual differences in age, sex, fitness, and baseline HRV. Compare yourself to your own recent history, and pay attention to the overall shape of the curve rather than any individual number. A single orange day sandwiched between a week of blue days is noise. A slow shift from mostly blue to mostly orange over a month is a signal.
How Wearable HRV Monitoring Evolved
HRV itself has been studied clinically for decades, but the idea that a consumer gadget on your wrist could track it meaningfully is recent. The shift happened in the 2010s, when wearable technology moved HRV monitoring out of the controlled setting of laboratories and clinics and into everyday life.19Biomedical Signal Processing and Control. Evolution of Heart Rate Variability (HRV) Analysis Methodologies (2000–2025): From Task Force Standards to Wearables, AI, and Clinical Translation Garmin was one of the first major consumer companies to bake a continuous stress feature into its product line, thanks to its partnership with (and eventual acquisition of) Firstbeat. Competitors have since introduced their own versions, with Apple, Samsung, and Fitbit all incorporating HRV-derived features, though each uses different algorithms and presents the information differently.
The gap between what clinical HRV measurement can tell a cardiologist and what a wrist sensor can tell you at home remains wide. Clinical recordings use ECG-derived R-R intervals with millisecond precision, often over 24 hours under semi-controlled conditions. A wrist sensor uses an optical proxy, with lower temporal resolution, in an uncontrolled environment where you are cooking dinner and scratching your arm. That gap will narrow as sensor hardware improves and algorithms become better at filtering noise, but it is important to keep in mind. Your Garmin stress score is a useful approximation from a consumer device. It is not a medical measurement, and treating it as one leads to either unnecessary anxiety or unwarranted reassurance.
The Nighttime HRV Number on Newer Garmin Watches
Starting in 2022, Garmin began displaying a separate overnight HRV metric distinct from the stress score. This number, labeled “HRV Status” on newer models, shows your average overnight RMSSD value over a rolling seven-day window and classifies it as balanced, low, or optimal relative to your personal history. RMSSD is the same metric researchers use to quantify parasympathetic activity, so this is arguably a more transparent presentation of the raw data than the stress score, which rolls multiple inputs together behind a proprietary curtain.
If you have access to both features, the overnight HRV Status is generally more stable and informative than daytime stress readings, for all the measurement-environment reasons already described. It also tends to respond more slowly to changes, which can be either a strength (less noise, fewer false alarms) or a weakness (slower to flag acute problems). Many athletes and coaches have gravitated toward the overnight HRV number as a guide for training readiness, using it to decide whether to push hard or take a recovery day. The stress score, meanwhile, remains more useful for recognizing acute lifestyle patterns: a bad night of sleep, the physiological aftermath of alcohol, or the cumulative toll of a stressful workweek.