After having worn my smartwatch and smart ring nearly every day over the last couple of years, I have found that there is a good balance between appreciating the data on my wrist and viewing it with some healthy skepticism. For example, one morning, my watch will show that I have slept “excellently” and burned a lot of calories from simply taking a walk. The following morning, I feel exhausted despite having recovered “perfectly.”
Sounds familiar?
Most of us bought these devices hoping for accurate readings about our steps, heart rate, sleep and recovery. However, not all sensors give similar results. Some readings are quite good in terms of their accuracy, but others can be described as mere approximations. Based on current research to determine the validity and reliability of these devices as compared to laboratory testing equipment (ECG chest strap, sleep tests), here is a breakdown of what you can actually trust and what data is best taken with a grain of salt.
How Wearable Sensors Actually Work
Most wearable devices rely on a small set of sensors that are the core of all the data we get from our devices.
PPG (Optical Heart Rate Sensors)- PPGs use green, red/infrared light to measure variations in blood volume underneath your skin. These provide HR, RHR, HRV, blood oxygen and recovery data.
Accelerometers and Gyroscopes (Motion Sensors)- These measure movement to track the number of steps, estimate the intensity of activity and differentiate between sleep and awake stages.
Additional Sensors- These include sensors like skin temperature, ECG, EDA or ambient light to detect cycle phases, stress, onset of an illness, readiness score or any more advanced features.
The raw data is then analyzed through an algorithm that produces the graphs and score values we use. The device is remarkable for its small size and the amount of information it packs, but many factors in the real world can affect the accuracy of data.
Heart Rate: Often Reliable, But Not During Chaos
For resting and light daily activity, PPG readings of heart rate from the wrist-worn trackers have proven to be accurate. These usually had an average error of less than 1 BPM in resting conditions. The Apple Watch has consistently performed better and has excellent correlation coefficients; Garmin and other Fitbit trackers also provide reliable HR estimates.
However, for high-intensity exercises, HIIT, resistance training and wrist-intensive activities such as cycling or typing, the accuracy of the PPG measurements significantly drops. Errors increase and many trackers have an absolute deviation of 10-20%+. Multiwavelength sensors have helped mitigate the problem, although recent studies have found that motion artifacts are more influential than skin color differences.
Trust or not: Should be trusted for resting HR and steady state cardio. Best paired with a chest strap for an accurate high-motion workout reading, especially if you’re training for a marathon or are an athlete.
Step Counting: One of the Most Dependable Metrics
Step counting appears to be quite reliable, particularly when walking and running occur under lab conditions. Garmin and Apple Watch can obtain less than 5% accuracy during experiments.
In their “free-living” version, the percentage of inaccuracy amounts to** 6-18%**. Walking, running, pushing a stroller, carrying things and cycling are harder to detect accurately. Since the Oura Ring is finger-based, it may count differently compared to a wrist tracker such as a WHOOP or an Apple Watch.
Trust or not: Very high. Relatively low in the case of non-standard days. For me, it was quite motivating despite inaccuracies in step counts.
Calorie Burn or Energy Expenditure: Treat as a Rough Guide
Calories burned are always a poor indicator in wearable tech. Research indicates mistakes of 20% to 50% or higher since calories cannot be determined directly but must be approximated based on factors such as heartbeat, activity levels, age, body mass index and general algorithms without knowledge of the individual’s metabolism, physical condition and muscle efficiency.
While the Apple Watch usually fares better than most, it still misses by several hundred calories on occasion.
Trust or not: Low when making calculations for everyday life decisions, such as calorie intake.
Sleep Tracking: Strong on Big Picture, Weaker on Details
Sleep/wake detection is another area where wearables, especially smart rings excel. Among various wearables tested by independent researchers, the Oura Ring always scores the highest accuracy (agreement with polysomnography). In one of the studies, the Oura ring 4 demonstrated an excellent Cohen’s kappa of 0.65 for its four-stage analysis (0.60 for Apple Watch, 0.55 for Fitbit), as well as high deep sleep sensitivity (~79.5%).
Yet, all wrist wearables usually overestimate sleep duration and efficiency (by 10-15%), not to mention relatively low accuracy in sleep stage distribution (REM, light, deep).
Trust or not: High for general duration, consistency levels and sleep/wake state. Moderate for a specific percentage per sleep cycle stage. Your “readiness” score for each night only truly comes into context after understanding how it correlates to how you feel the next day.
HRV, SpO2 and Other Metrics
Heart Rate Variability (HRV) and Recovery:
Oura devices excel in this category, particularly at night, where they achieve a high concordance correlation coefficient of up to 0.99 and very low error rates (about 6%) compared to ECGs in 2025 trials.
Blood Oxygen Saturation (SpO2):
Acceptable at rest but susceptible to dropouts when exercising or at high altitudes.
Skin Temperature:
Useful for observing relative fluctuations (disease, menstrual cycle changes) rather than absolute values.
Real-Life Factors That Affect Accuracy
Problems include loose fitting, sweat, tattoos, positioning of the wrist during exercise and the type of movement. Motion artifacts continue to be the problem despite the efforts by manufacturers to minimize errors due to skin tone differences in modern sensors. The wearable device never receives calibration in a laboratory setting.
Simple Habits That Make My Data More Reliable
Here are some simple techniques that will be useful to you without any additional gadgets:
Give preference to trends over daily fluctuations – An occasional spike is not important, but it is a different story when the values and trends are elevated for two weeks.
Add your own notes – Log information about the performance level of your training (on a scale from 1 to 10), energy level or actual sleeping and waking hours, what factors affected them, traveling, etc. The application calculates new baselines based on this information.
Combine sources – Utilize the phone GPS for walking outside, while the cheapest chest strap will measure heart rate for intense workouts. Multiple sensors' data is automatically combined by many health applications.
Perform quick reality checks – Twice a year, cross-check readings against your chest strap at least once in the context of exercise or create a manual sleeping schedule for several days.
Use the right gadget for the purpose you want to solve – Oura ring is perfect for monitoring sleep and recovery, whereas Garmin or Apple watches are better for training and tracking your distance.
The Bottom Line: Smart Use Beats Perfect Hardware
None of these consumer wearables qualify as medical devices, nor will their next-gen versions be any different. The accuracy of heart rate measurements while awake, step count, general sleep tendencies and overnight HRV values can be relied upon. Calorie expenditure and sleep stage detection can be useful but still fall into a "helpful indicator" category, not perfect measurements.
If you use the data in tandem with how you actually feel, that would be the real gold mine. The use of consumer wearables has been highly motivational for me. For example, my Ultrahuman Ring has helped me realize my late-night snacking habits were affecting my heart rate drop during sleep, something which I previously did not pay much heed to.
Do you think some of the metrics in your wearable are more or less accurate than others? What kind of wearable do you have and what makes you believe its information? Let me know in the comments below.
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