Accuracy of Wearable Technology & Smart Watches

Key TAKEAWAYS

‍3.5% of biometric outcomes have been validated for all of the biometric outcomes they report
11% of consumer wearables have been validated for at least one biometric outcome
44% of people use wearable fitness devices to measure heart rate.
42% of people use wearable fitness devices to measure caloric expenditure (calories burned).
On average, wearable fitness devices have a slight tendency to underestimate heart rate.
On average, there is a tendency for wearable fitness devices to underestimate caloric expenditure.
Exercise intensity, motion of extremities during exercise, wrist position, interference between skin and sensors (sweat or dirt on the skin), and skin pigmentation have been shown to decrease the accuracy of wearable devices.
60% of people use wearable fitness devices to track step count.
On average, wearable fitness devices underestimate step count by 9%.‍
The majority of wearable fitness devices overestimate total sleep time and sleep efficiency by 10% and underestimate wakefulness after sleep onset.
On average, wearable fitness devices overestimate aerobic capacity (VO2max) by 15% at rest and up to 10% during exercise tests.
Meta-analyses show most wearables can accurately predict COVID-19 detection 80.2% of the time, atrial fibrillation by 87.4%, and fall detection by 81.9%.

Contents

For further analysis, we broke down the data by wearable device:

In the rapidly growing sport of pickleball, athletes are turning to wearable technology to gain valuable insights into their performance and recovery. These devices track critical data such as heart rate, sleep patterns, and energy expenditure—pivotal in optimizing an athlete's preparation and performance on the court. However, the effectiveness of these devices hinges on one critical factor—accuracy.

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Inaccurate wearable data can lead to misguided training intensities, improper energy management, a drop in cognitive sharpness, and, ultimately, subpar performance. When accuracy is prioritized, wearables provide reliable information to tailor your workouts and ensure adequate rest, helping you perform your best on and off the court.

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AIM7 turns your wearable and HRV data into ultra-personalized plans for exercise, recovery, and mental fitness.

AIM7 unlocks the power of your wearable device by turning your data into actionable recommendations and plans to help you look, feel, and perform your best.

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Smart Watch Accuracy Table 1: Heart Rate, Caloric Expenditure, Step Count and Sleep Tracking

Note: Swipe left and right to view table.

	Expert Advice	Expert Rating
Heart Rate	Accuracy decreases with increasing intensity. Helpful to track resting heart rate over time to monitor for sickness or over training. Helpful to monitor heart rate over time doing similar activities to see if there are any deviations from the norm.	★★★★☆
Caloric Expenditure	There is a chance of over/underestimation. With options for goal setting, reminders to move, and social support, clinicians may find wearables useful to help patients initially monitor calories consumed and physical activity completed to determine behavioral changes needed.	★★★☆☆
Step Count	There are differences in the accuracy of step count measurement depending on the device being utilized. It can be useful to track steps over time to improve activity. Tracking step count could demotivate people if goals are not being achieved.	★★★☆☆
Sleep Tracking	There are concerns from sleep specialists regarding the use of wearable devices to measure sleep. Concerns mount over what they call orthosomnia- the desire to perfect sleep. (typically through monitoring using wearable devices) In their opinion, some users rely too heavily on their devices to measure sleep, and overestimate the validity of said devices.	★★☆☆☆

Table 1 highlights specific advice and ratings given by experts on the capabilities of wearable technology to measure heart rate, caloric expenditure, step count, and sleep tracking.

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Apple Watch Accuracy: Calories, Heart Rate, Steps and Sleep

Apple watches have been shown to underestimate heart rate by an average of 1.3 beats per minute during exercise.
Contrary to other wearable fitness devices, during graded exercise testing Apple watch accuracy improves as heart rate increases.
During graded exercise testing Apple watches have been shown to miscalculate caloric expenditure by as much as 115%.
Apple Watch 6 tends to overestimate energy expenditure, with a mean percent error ranging from –6.61% to 53.24%‍
On average, the Apple watches have a 0.9-3.4% error when measuring total step count.
Apple watches correctly identify when a person is sleeping 97% of the time when monitoring sleep.
Apple watches correctly identify when someone wakes up during sleep only 26% of the time.
On average, Apple Watches underestimate heart rate variability by 9.6 ms.

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Oura Ring Accuracy: Calories, Heart Rate, Steps and Sleep

The Oura ring has demonstrated 99.3% accuracy for measuring resting heart rate.
On average, the Oura ring demonstrated 91.5% accuracy measuring RMSSD.
On average, the Oura ring tended to underreport resting heart rate by 1 beat per minute.
On average, the device demonstrated a 13% error when measuring caloric expenditure.
On average, the Oura ring underestimates energy expenditure, with increased discrepancy as intensity increases.
The Oura ring correctly identifies when a person is sleeping 94% of the time when monitoring sleep.
Oura ring’s sleep algorithm calculates total sleep time with 96% accuracy.
Oura ring’s sleep algorithm correctly identifies time spent in light, deep, wake, and rem sleep 79% of the time. Deep and REM sleep stages are the most accurate.
The Oura ring correctly identifies when someone wakes up during sleep 57% of the time.
On Average, Oura ring underestimated heart rate variability by 10.2 ms.
On average, the Oura ring demonstrates a 50.3% error when measuring step count when measured in the real world.
On average the Oura ring demonstrates a 4.8% error when measuring step count.
Oura Rings worn on the non-dominant- and dominant-hand underestimated sleep efficiency by 1.1 %–1.5 % and time spent in REM sleep by 4.1–5.6 min.

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WHOOP Accuracy: Heart Rate and Sleep

On average heart rate measurements performed by WHOOP are 99.7% accurate.
WHOOP is 99% accurate when measuring heart rate variability, with an average underestimated of just 4.5 ms.
Other research has shown WHOOP to have a high degree of consistency when measuring heart rate and heart rate variability.
WHOOP correctly identifies when a person is sleeping 90% of the time when monitoring sleep.
WHOOP correctly identifies when someone wakes up during sleep 56% of the time.
WHOOP claims that their product does not count steps because step count because it ignores intensity and other movements. Their preferred method is “strain,” which takes into account simultaneous heart rate with physical activity or activities of daily living.
WHOOP deviated the least compared to the gold-standard PSG (against Garmin and FitBit) for total sleep time, light sleep, and deep sleep but overestimated REM sleep by 21 minutes on average.

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Garmin Accuracy: Calories, Heart Rate, Steps and Sleep

On average Garmin has been shown to have a 1.16-1.39% error when measuring heart rate.
Literature has shown that Garmin has a 6.1-42.9% error when measuring caloric expenditure.
When measuring step count, literature demonstrates that Garmin has an average measurement error of 23.7%.
Garmin correctly identifies when a person is sleeping 98% of the time when monitoring sleep.
Garmin correctly identifies when someone wakes up during sleep only 27% of the time.
On average, Garmin underestimated heart rate variability by 22.4 ms. The Garmin Vivo Smart 4 showed a mean overestimation of 46.9 minutes for total sleep time, a mean overestimation of 27.9 minutes for light sleep, a mean overestimation of 23.5 minutes for deep sleep, and a mean underestimation of 12.5 minutes for REM sleep.

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Fitbit Accuracy: Calories, Steps and Sleep

Fitbit has been shown to underestimate heart rate by an average of 9.3 beats per minute during exercise.
On average Fitbit displays a 14.8% error when measuring caloric expenditure.
On average, Fitbit miscalculates step count by 9.1-21.9%.
Fitbit devices tend to overestimate total sleep time by 7-67 minutes.
Fitbit Charge 4 overestimates REM sleep by only 4 minutes; however, the wrist-worn device overestimates light sleep by 37.6 minutes.

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Samsung Accuracy: Calories, Heart Rate and Steps

Samsung devices have been shown to underestimate heart rate by an average of 7.1 beats per minute during exercise.
Samsung devices display a 1.08-6.30% error when measuring step count.
On average, Samsung devices have been shown to have a 9.1-20.8% error when measuring energy expenditure.
On average, Samsung devices underreport heart rate variability by 18.24 ms.
The Galaxy Watch 3 (wrist-worn device) reported accurate sleep stages 65% of the time.
Cuffless blood pressure readings show an average pre-post calibration error for systolic BP of 6.8 ± 5.6 mmHg, which increases with higher systolic BP levels.

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Polar (Wrist and Arm) Accuracy: Calories, Heart Rate and Sleep

On average, Polar wearable fitness devices placed on the upper arm had a 2.2% error when measuring heart rate.
Polar wrist worn devices correctly identify when a person is sleeping 92% of the time when monitoring sleep.
Polar wrist worn devices correctly identify when someone wakes up during sleep 51% of the time.
On average, Polar wrist worn devices underestimate heart rate variability by 8.7 ms.
On average, wrist worn polar devices have been shown to have a 16.7% error when measuring caloric expenditure during moderate intensity exercise.
On average, wrist-worn polar devices have been shown to have a 10% error when measuring caloric expenditure during moderate-intensity exercise, underestimating energy expenditure with a mean percent error ranging from –3.51 % to 11.33 %.

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Withings Accuracy: Calories, Heart Rate, Sleep and Steps

Withings ScanWatch measures heart rate with 3-11% error during free-living activities.
On average, the Withings Pulse O2 device calculates energy expenditure with 20-98% error.
On average, the Withings Pulse O2 device measures total sleep time with a 6% error, but the error rate has been shown to be as much as 56% in some instances.
On average, wrist worn Withings Pulse Ox estimates step count with a 0.7-58.3% error.

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Error Comparison: Apple Watch, Oura Ring, WHOOP, Garmin, Fitbit, Samsung, Polar and Withings

‎🟩 ≤ 10 % error

🟨 10.1-25% error

🟥 ≥ 25.1% error

⬛ No Data Available

Note: Swipe left and right to view table.

	Caloric Expenditure	Heart Rate	Steps	Sleep
Apple Watch	115%	.91%	3.4%	3%
Oura Ring	13%	3%	4.8%	6%
Whoop		0.3%		10%
Garmin	42.9%	1.39%	23.7%	2%
Fitbit	14.8%		21.9%	13%
Samsung	20.8%	1.1%	6.3%
Polar	16.7%	2.2%		8%
Withings	98%	11%	58.3%	6%

Caloric Expenditure: Average % error of Caloric Expenditure when compared to the gold standard measurement.
Heart rate: Average % error of heart rate when compared to the gold standard measurement.
Steps: Average % error of step count when compared to the gold standard measurement.
Sleep: Average %error of identifying sleep versus wakefulness compared to the gold standard measurement.
**All error % are based on the worst possible condition demonstrated in the literature cited

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Conclusion: How Accurate are Smart Watches?

The information presented in this blog is sourced from the references cited . The values reported represent the ‘worst case scenario’ from the literature reviewed. The relative error of each device may differ from the reported values during real world application because the values reported are an average of a sample collected in a particular study. Overall, each of these devices is relatively inconsistent when measuring biometric data. The measurement capability of wearable fitness devices has improved tremendously and with further improvements in technology, it is expected to get even better.

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Accuracy of Wearable Technology & Smart Watches

Key Takeaways:

AIM7 turns your wearable and HRV data into ultra-personalized plans for exercise, recovery, and mental fitness.

AIM7 unlocks the power of your wearable device by turning your data into actionable recommendations and plans to help you look, feel, and perform your best.

Smart Watch Accuracy Table 1: Heart Rate, Caloric Expenditure, Step Count and Sleep Tracking

Expert Advice

Expert Rating

Apple Watch Accuracy: Calories, Heart Rate, Steps and Sleep

Oura Ring Accuracy: Calories, Heart Rate, Steps and Sleep

WHOOP Accuracy: Heart Rate and Sleep

Garmin Accuracy: Calories, Heart Rate, Steps and Sleep

Fitbit Accuracy: Calories, Steps and Sleep

Samsung Accuracy: Calories, Heart Rate and Steps

Polar (Wrist and Arm) Accuracy: Calories, Heart Rate and Sleep

Withings Accuracy: Calories, Heart Rate, Sleep and Steps

Error Comparison: Apple Watch, Oura Ring, WHOOP, Garmin, Fitbit, Samsung, Polar and Withings

Caloric Expenditure

Heart Rate

Steps

Sleep

Conclusion: How Accurate are Smart Watches?

Smart Watch Accuracy References:

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AIM7 turns your wearable and HRV data into ultra-personalized plans for exercise, recovery, and mental fitness.

AIM7 unlocks the power of your wearable device by turning your data into actionable recommendations and plans to help you look, feel, and perform your best.

Smart Watch Accuracy Table 1: Heart Rate, Caloric Expenditure, Step Count and Sleep Tracking

Expert Advice

Expert Rating

Apple Watch Accuracy: Calories, Heart Rate, Steps and Sleep

Oura Ring Accuracy: Calories, Heart Rate, Steps and Sleep

WHOOP Accuracy: Heart Rate and Sleep

Garmin Accuracy: Calories, Heart Rate, Steps and Sleep

Fitbit Accuracy: Calories, Steps and Sleep

Samsung Accuracy: Calories, Heart Rate and Steps

Polar (Wrist and Arm) Accuracy: Calories, Heart Rate and Sleep

Withings Accuracy: Calories, Heart Rate, Sleep and Steps

Error Comparison: Apple Watch, Oura Ring, WHOOP, Garmin, Fitbit, Samsung, Polar and Withings

Caloric Expenditure

Heart Rate

Steps

Sleep

Conclusion: How Accurate are Smart Watches?

Smart Watch Accuracy References:

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Micro Workouts, Sustainable Fitness, & Winning the Scoreboard of Stress with Brad Kearns

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