1258 Is My Sleep Tracker Tracking My (REM) Sleep? Comparison of Two Consumer Smartwatch Devices to Polysomnogram, in a Sleep Clinic Referral Population

Abstract Introduction The popularity of consumer sleep-tracker smartwatch technology continues to grow, but uncertainty remains over data accuracy and applicability to patients with sleep disorders. Methods Subjects undergoing evaluation for sleep disorders at a single sleep center (Wyomissing, PA), during a 16-month period ending September 2025, were enrolled in the study on the night of their scheduled polysomnogram (PSG). Subjects wore Fitbit Inspire 3 (FBI3) and Garmin VivoSmart 5 (GVS5) sleep-tracker devices during the PSG. Summary sleep staging data (total rapid eye movement [REM] sleep and total sleep time [TST]) were analyzed by descriptive statistics, paired Student's t-Test, and equivalence testing (using Two One-Sided Tests [TOST]), versus gold-standard PSG. Results A total of 110 subjects enrolled; 92 provided complete data. Subjects were excluded from the analysis due to early termination of PSG (n=2) or sleep-tracker device failure (FBI3 [n=13]; GVS5 [n=8]). Total minutes of REM sleep mean +/- standard deviation (SD) were similar across devices: PSG 66.9 (SD 30.7), FBI3 70.0 (SD 27.5) and GVS5 70.0 (SD 44.5) minutes. Paired Student's t-Test showed no significant difference in PSG total REM sleep compared to FBI3 (t=0.95, p=0.35) or GVS5 (t=0.63, p=0.53). Testing of equivalence using TOST (employing prespecified 90% upper and lower confidence intervals of +/- 10 minutes), demonstrated that FBI3-measured REM sleep was equivalent (i.e., no substantial differences in means) to PSG-measured REM (mean difference –3.1 min [CI -8.5; +2.3]); GVS5 sleep-tracker did not meet equivalence (mean difference -3.1 min [-11.3; +5.1]). Sleep-tracker devices measured total sleep time with comparatively less accuracy: PSG 355.1 (SD 69.8) minutes; FBI3 365.9 (SD 77.1) minutes; GVS5 444.9 (SD 73.0) minutes. Although the FBI3 device-measured total sleep time did not differ significantly from PSG (Student's t-Test [t=1.50, p=0.138]), the GVS5 device highly overestimated TST (t=10.4, p< 0.01]). Conclusion Among sleep medicine patients, sleep-tracker smartwatches provided potentially clinically relevant estimates of total REM sleep, but showed wider variability in measurements of total sleep time, depending on the device, compared to the gold-standard polysomnogram. Support (if any) The Reading Hospital Foundation (Reading, PA) provided grant funding.

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Publication Details

Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.1257
Primary Topic
Sleep and related disorders
Type
article
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article

1258 Is My Sleep Tracker Tracking My (REM) Sleep? Comparison of Two Consumer Smartwatch Devices to Polysomnogram, in a Sleep Clinic Referral Population

Umer Shoukat, Roopika Reddy, Pratap Reddy, Ana Rocha et al.
SLEEP
Sleep and related disorders
article

1258 Is My Sleep Tracker Tracking My (REM) Sleep? Comparison of Two Consumer Smartwatch Devices to Polysomnogram, in a Sleep Clinic Referral Population

Umer Shoukat, Roopika Reddy, Pratap Reddy, Ana Rocha, Sushmita Shrestha, Alec Platt, Eric Abreu, Thomas Wasser
article en

Abstract

Abstract Introduction The popularity of consumer sleep-tracker smartwatch technology continues to grow, but uncertainty remains over data accuracy and applicability to patients with sleep disorders. Methods Subjects undergoing evaluation for sleep disorders at a single sleep center (Wyomissing, PA), during a 16-month period ending September 2025, were enrolled in the study on the night of their scheduled polysomnogram (PSG). Subjects wore Fitbit Inspire 3 (FBI3) and Garmin VivoSmart 5 (GVS5) sleep-tracker devices during the PSG. Summary sleep staging data (total rapid eye movement [REM] sleep and total sleep time [TST]) were analyzed by descriptive statistics, paired Student's t-Test, and equivalence testing (using Two One-Sided Tests [TOST]), versus gold-standard PSG. Results A total of 110 subjects enrolled; 92 provided complete data. Subjects were excluded from the analysis due to early termination of PSG (n=2) or sleep-tracker device failure (FBI3 [n=13]; GVS5 [n=8]). Total minutes of REM sleep mean +/- standard deviation (SD) were similar across devices: PSG 66.9 (SD 30.7), FBI3 70.0 (SD 27.5) and GVS5 70.0 (SD 44.5) minutes. Paired Student's t-Test showed no significant difference in PSG total REM sleep compared to FBI3 (t=0.95, p=0.35) or GVS5 (t=0.63, p=0.53). Testing of equivalence using TOST (employing prespecified 90% upper and lower confidence intervals of +/- 10 minutes), demonstrated that FBI3-measured REM sleep was equivalent (i.e., no substantial differences in means) to PSG-measured REM (mean difference –3.1 min [CI -8.5; +2.3]); GVS5 sleep-tracker did not meet equivalence (mean difference -3.1 min [-11.3; +5.1]). Sleep-tracker devices measured total sleep time with comparatively less accuracy: PSG 355.1 (SD 69.8) minutes; FBI3 365.9 (SD 77.1) minutes; GVS5 444.9 (SD 73.0) minutes. Although the FBI3 device-measured total sleep time did not differ significantly from PSG (Student's t-Test [t=1.50, p=0.138]), the GVS5 device highly overestimated TST (t=10.4, p< 0.01]). Conclusion Among sleep medicine patients, sleep-tracker smartwatches provided potentially clinically relevant estimates of total REM sleep, but showed wider variability in measurements of total sleep time, depending on the device, compared to the gold-standard polysomnogram. Support (if any) The Reading Hospital Foundation (Reading, PA) provided grant funding.

SLEEPVol. 49(Supplement_1)
DM-STAT (United States) (US), Dermatology Specialists (US), Baylor Scott & White Health (US), Rowan University (US)
Openalex Percentile: Top 6%
Sleep and related disorders
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