---
title: "Garmin Forerunner 265 — Evidence, Benefits & Where to Buy | Magellan"
description: "Garmin Forerunner 265 — Consumer biometric wearables—smartwatches, wrist-worn bands and finger rings from makers such as Apple, Garmin, Fitbit, WHOOP,…"
url: "https://magellanlongevity.com/p/65.md"
canonical: "https://magellanlongevity.com/p/65.html"
html: "https://magellanlongevity.com/p/65.html"
type: "product"
section: "Biometric Wearables & Sensors"
evidence_grade: "Measurement tool"
evidence_tier: "tool"
citations: 104
product_id: 65
price_usd: 449.99
updated: 2026-09-02
author: "Gabriel Radu, DO"
author_credentials: "Physiatrist (PM&R). NY medical license 275110. NPI 1376861765."
publisher: "Magellan Longevity"
content_format: "markdown"
license: "Educational content — not medical advice"
---

# Garmin Forerunner 265

[Home](https://magellanlongevity.com/) › [Biometric Wearables & Sensors](https://magellanlongevity.com/c/4.md) › Garmin Forerunner 265

**HTML version:** https://magellanlongevity.com/p/65.html · **In the Magellan app:** https://magellanlongevity.com/#/product/65

## Key facts

| Field | Value |
| --- | --- |
| Product | Garmin Forerunner 265 |
| Category | [Biometric Wearables & Sensors](https://magellanlongevity.com/c/4.md) |
| Evidence grade | Measurement tool (B) |
| Peer-reviewed citations | 104 |
| Typical listed price | $449.99 (check the live price) |
| Where to buy | [Search Amazon](https://www.amazon.com/s?k=Garmin%20Forerunner%20265&tag=magellanlong-20) |
| Catalog ID | 65 |

## What it is

Consumer biometric wearables—smartwatches, wrist-worn bands and finger rings from makers such as Apple, Garmin, Fitbit, WHOOP, Polar and Oura—use photoplethysmography, accelerometry and, in some models, temperature, electrodermal or single-lead-ECG sensors to continuously estimate sleep and sleep stages, resting and nocturnal heart rate, heart-rate variability (HRV), respiratory rate, skin temperature and daily activity. Validation research compares these readings against gold-standard polysomnography and electrocardiography. The signals they report—sleep duration, resting heart rate, HRV, step count and cardiorespiratory fitness—are physiological markers that large epidemiological studies link to long-term health, cardiovascular risk and mortality.

## Its role in longevity

Across brands, independent validations find these devices agree closely with polysomnography for sleep-versus-wake detection and with ECG for heart rate and time-domain HRV (RMSSD), while four-stage sleep staging is only moderate (roughly 50-75% agreement) and energy-expenditure estimates are poor; several validation studies are industry-funded. Atrial-fibrillation screening is validated at scale—the Apple and Fitbit heart studies each enrolled over 400,000 people and found high positive predictive value for irregular-rhythm notifications—though confirmatory single-lead ECG has only modest sensitivity, and false alerts can undermine users' well-being. Activity trackers as a class modestly increase physical activity (about 1,800 extra steps per day in an umbrella review of 39 meta-analyses), and the biomarkers they track—resting heart rate, sleep duration, daily steps, cardiorespiratory fitness and HRV—robustly predict mortality in cohort research. Importantly, no study shows that wearing any of these devices or acting on their data lengthens lifespan; this evidence concerns the underlying biomarkers and the devices' measurement accuracy, not these specific commercial products.

## Evidence grade: Measurement tool

- **What the grade means:** Graded as an instrument: how accurately it measures, and whether measuring it changes anything.
- **Dose used in studies:** Use it for pace, distance and steps; pair a chest strap for interval and threshold work, because wrist optical heart rate lags at high intensity. Treat the VO2max estimate as a rough training marker and re-check it against an actual field test rather than reading it as a fitness score.
- **What this grade does not say:** Garmin's optical heart rate is among the better performers at rest and steady state and its GPS-derived pace and distance hold up, but no brand measures energy expenditure accurately, and a Garmin watch running the same submaximal-run algorithm underestimated laboratory gas-analysis VO2max by about 4.7 mL/kg/min, with the error roughly twice as large in the fittest runners. Sleep is the weak point: Garmin devices scored worse than research actigraphy on sleep/wake detection, and against polysomnography a Garmin multisport watch overestimated total sleep time by roughly 85 minutes and significantly misassigned sleep stages, overcalling light sleep and undercalling deep. Worth being blunt about: the Forerunner 265 does not have Garmin's FDA-cleared ECG app, which requires hardware only present on certain other models, so this watch has no rhythm-detection feature at all. The metric here with genuinely strong outcome evidence is steps, and that evidence is about steps rather than about any particular watch.

## In the news

- **Wearable Sensor May Signal You're Developing COVID-19 – Even If Your Symptoms Are Subtle** — UC San Francisco 2020 [Read it](https://www.ucsf.edu/news/2020/12/419271/wearable-sensor-may-signal-youre-developing-covid-19-even-if-your-symptoms-are)
  > An analysis of data from 50 people previously infected with COVID-19, published online in the peer-reviewed journal Scientific Reports on Dec. 14, 2020, found that data obtained from the commercially available smart ring accurately identified higher temperatures in people with symptoms of COVID-19.
- **Oura Ring, Apple Watch, and Fitbit Tested Against PSG in Sleep Accuracy Study** — Sleep Review 2024 [Read it](https://sleepreviewmag.com/sleep-diagnostics/consumer-sleep-tracking/wearable-sleep-trackers/oura-ring-apple-watch-fitbit-face-off-sleep-accuracy-study/)
  > A study evaluating the accuracy of sleep-staging algorithms in three consumer wearable devices—Oura Ring, Fitbit Sense, and Apple Watch—against gold-standard polysomnography found that Oura Ring was the most accurate sleep tracker in four-stage sleep classification.
- **What is heart rate variability?** — Harvard Health 2021 [Read it](https://www.health.harvard.edu/heart-health/what-is-heart-rate-variability)
  > Perhaps not surprisingly, low HRV is associated with an increased risk of cardiovascular disease. People with high HRV, on the other hand, tend to have higher fitness levels and be more resilient to stress.
- **Heart Rate Variability (HRV): What It Is and How You Can Track It** — Cleveland Clinic 2021 [Read it](https://my.clevelandclinic.org/health/symptoms/21773-heart-rate-variability-hrv)
  > In general, low heart rate variability is considered a sign of current or future health problems because it shows your body is less resilient and struggles to handle changing situations.
- **Abnormal resting heart rate over long term may predict future heart failure or death** — American Heart Association News 2024 [Read it](https://www.heart.org/en/news/2024/11/22/abnormal-resting-heart-rate-over-long-term-may-predict-future-heart-failure-or-death)
  > After accounting for known cardiovascular risk factors, people whose resting heart rate increased slightly or sharply were 65% more likely to develop heart failure than those whose resting heart rate decreased slightly over the study period, and 69% more likely to die from any cause.
- **Through Apple Heart Study, Stanford Medicine researchers show wearable technology can help detect atrial fibrillation** — Stanford Medicine 2019 [Read it](https://med.stanford.edu/news/all-news/2019/11/through-apple-heart-study--stanford-medicine-researchers-show-we.html)
  > Wearable technology can safely identify heart rate irregularities that subsequent clinical evaluations confirmed to be atrial fibrillation

## The research

Peer-reviewed studies on the active compound. Quotes are verbatim from the cited abstract. Research describes the active mechanism and is not a claim about this specific product.

### Cited studies

1. **The impact of visit-to-visit heart rate variability on all-cause mortality**
   Annals of Noninvasive Electrocardiology 2024 · [PMID 38288511](https://pubmed.ncbi.nlm.nih.gov/38288511/) · [DOI 10.1111/anec.13094](https://doi.org/10.1111/anec.13094)

   > Previous studies have shown a positive correlation between heart rate variability and clinical outcomes, including all-cause mortality.

2. **Sleep duration and risk of all-cause mortality: a systematic review and meta-analysis**
   Epidemiology and Psychiatric Sciences 2018 · [PMID 30058510](https://pubmed.ncbi.nlm.nih.gov/30058510/) · [DOI 10.1017/S2045796018000379](https://doi.org/10.1017/S2045796018000379)

   > Both short and long sleep duration were associated with an increased risk of all-cause mortality in this meta-analysis.

3. **Heart Rate Variability and Risk of All-Cause Death and Cardiovascular Events in Patients With Cardiovascular Disease: A Meta-Analysis**
   Biol Res Nurs 2019 · [PMID 31558032](https://pubmed.ncbi.nlm.nih.gov/31558032/) · [DOI 10.1177/1099800419877442](https://doi.org/10.1177/1099800419877442)

   > lower heart rate variability was associated with a higher risk of all-cause death and cardiovascular events

4. **Accuracy of Three Commercial Wearable Devices for Sleep Tracking in Healthy Adults.**
   Sensors (Basel) 2024 · [PMID 39460013](https://pubmed.ncbi.nlm.nih.gov/39460013/) · [DOI 10.3390/s24206532](https://doi.org/10.3390/s24206532)

   > The Oura ring was not different from PSG in terms of wake, light sleep, deep sleep, or REM sleep estimation.

5. **Validity and reliability of the Oura Ring Generation 3 (Gen3) with Oura sleep staging algorithm 2.0 (OSSA 2.0) when compared to multi-night ambulatory polysomnography: A validation study of 96 participants and 421,045 epochs.**
   Sleep Med 2024 · [PMID 38382312](https://pubmed.ncbi.nlm.nih.gov/38382312/) · [DOI 10.1016/j.sleep.2024.01.020](https://doi.org/10.1016/j.sleep.2024.01.020)

   > The Oura Ring Gen3 with OSSA 2.0 shows good agreement with PSG for global sleep measures and time spent in light and deep sleep.

6. **Accuracy of 11 Wearable, Nearable, and Airable Consumer Sleep Trackers: Prospective Multicenter Validation Study.**
   JMIR Mhealth Uhealth 2023 · [PMID 37917155](https://pubmed.ncbi.nlm.nih.gov/37917155/) · [DOI 10.2196/50983](https://doi.org/10.2196/50983)

   > epoch-by-epoch agreement in sleep stage classification showed substantial performance variation. More specifically, the highest macro F1 score was 0.69, while the lowest macro F1 score was 0.26.

7. **Multi-Night Validation of a Sleep Tracking Ring in Adolescents Compared with a Research Actigraph and Polysomnography.**
   Nat Sci Sleep 2021 · [PMID 33623459](https://pubmed.ncbi.nlm.nih.gov/33623459/) · [DOI 10.2147/NSS.S286070](https://doi.org/10.2147/NSS.S286070)

   > The Oura ring yielded comparable sleep measurement to research grade actigraphy at the latter's default settings. Sleep staging needs improvement.

8. **Accuracy Assessment of Oura Ring Nocturnal Heart Rate and Heart Rate Variability in Comparison With Electrocardiography in Time and Frequency Domains: Comprehensive Analysis.**
   J Med Internet Res 2022 · [PMID 35040799](https://pubmed.ncbi.nlm.nih.gov/35040799/) · [DOI 10.2196/27487](https://doi.org/10.2196/27487)

   > The Oura Ring could accurately measure nocturnal HR and RMSSD in both the 5-minute and average-per-night tests. It provided acceptable nocturnal AVNN, pNN50, HF, and SDNN accuracy in the average-per-night test but not in the 5-minute test.

9. **Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG.**
   Physiol Meas 2020 · [PMID 32217820](https://pubmed.ncbi.nlm.nih.gov/32217820/) · [DOI 10.1088/1361-6579/ab840a](https://doi.org/10.1088/1361-6579/ab840a)

   > Very high agreement between the ring and ECG was observed for nightly average HR and HRV (r= 0.996 and 0.980, respectively) with a mean bias of -0.63 bpm and -1.2 ms.

10. **Resting heart rate and all-cause and cardiovascular mortality in the general population: a meta-analysis.**
    CMAJ 2015 · [PMID 26598376](https://pubmed.ncbi.nlm.nih.gov/26598376/) · [DOI 10.1503/cmaj.150535](https://doi.org/10.1503/cmaj.150535)

    > The relative risk with 10 beats/min increment of resting heart rate was 1.09 (95% CI 1.07-1.12) for all-cause mortality and 1.08 (95% CI 1.06-1.10) for cardiovascular mortality.

11. **Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies.**
    Sleep 2010 · [PMID 20469800](https://pubmed.ncbi.nlm.nih.gov/20469800/) · [DOI 10.1093/sleep/33.5.585](https://doi.org/10.1093/sleep/33.5.585)

    > In the pooled analysis, short duration of sleep was associated with a greater risk of death (RR: 1.12; 95% CI 1.06 to 1.18; P < 0.01)

12. **Relationship of Sleep Duration With All-Cause Mortality and Cardiovascular Events: A Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies.**
    J Am Heart Assoc 2017 · [PMID 28889101](https://pubmed.ncbi.nlm.nih.gov/28889101/) · [DOI 10.1161/JAHA.117.005947](https://doi.org/10.1161/JAHA.117.005947)

    > U-shaped associations were indicated between sleep duration and risk of all outcomes, with the lowest risk observed for ≈7-hour sleep duration per day, which was varied little by sex.

13. **Sleep duration and mortality in the elderly: a systematic review with meta-analysis.**
    BMJ Open 2016 · [PMID 26888725](https://pubmed.ncbi.nlm.nih.gov/26888725/) · [DOI 10.1136/bmjopen-2015-008119](https://doi.org/10.1136/bmjopen-2015-008119)

    > In the pooled analysis, long and short sleep duration were associated with increased all-cause mortality (RR 1.33; 95% CI 1.24 to 1.43 and RR 1.07; 95% CI 1.03 to 1.11, respectively), compared with the reference category.

14. **Sleep Disturbance, Sleep Duration, and Inflammation: A Systematic Review and Meta-Analysis of Cohort Studies and Experimental Sleep Deprivation.**
    Biol Psychiatry 2015 · [PMID 26140821](https://pubmed.ncbi.nlm.nih.gov/26140821/) · [DOI 10.1016/j.biopsych.2015.05.014](https://doi.org/10.1016/j.biopsych.2015.05.014)

    > Sleep disturbance was associated with higher levels of CRP (ES .12; 95% CI = .05-.19) and IL-6 (ES .20; 95% CI = .08-.31).

15. **Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts.**
    Lancet Public Health 2022 · [PMID 35247352](https://pubmed.ncbi.nlm.nih.gov/35247352/) · [DOI 10.1016/S2468-2667(21)00302-9](https://doi.org/10.1016/S2468-2667%2821%2900302-9)

    > Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age.

16. **Prospective Association of Daily Steps With Cardiovascular Disease: A Harmonized Meta-Analysis.**
    Circulation 2022 · [PMID 36537288](https://pubmed.ncbi.nlm.nih.gov/36537288/) · [DOI 10.1161/CIRCULATIONAHA.122.061288](https://doi.org/10.1161/CIRCULATIONAHA.122.061288)

    > For older adults, the HR for quartile 2 was 0.80 (95% CI, 0.69 to 0.93), 0.62 for quartile 3 (95% CI, 0.52 to 0.74), and 0.51 for quartile 4 (95% CI, 0.41 to 0.63) compared with the lowest quartile.

17. **Daily Step Count and Depression in Adults: A Systematic Review and Meta-Analysis.**
    JAMA Netw Open 2024 · [PMID 39680407](https://pubmed.ncbi.nlm.nih.gov/39680407/) · [DOI 10.1001/jamanetworkopen.2024.51208](https://doi.org/10.1001/jamanetworkopen.2024.51208)

    > Pooled estimates from prospective cohort studies indicated that participants with 7000 or more steps/d had reduced risk of depression compared with their counterparts with fewer than 7000 steps/d (RR, 0.69; 95% CI, 0.62-0.77).

18. **Metrics from Wearable Devices as Candidate Predictors of Antibody Response Following Vaccination against COVID-19: Data from the Second TemPredict Study.**
    Vaccines (Basel) 2022 · [PMID 35214723](https://pubmed.ncbi.nlm.nih.gov/35214723/) · [DOI 10.3390/vaccines10020264](https://doi.org/10.3390/vaccines10020264)

    > increases in dermal temperature deviation and resting heart rate, and decreases in heart rate variability (a measure of sympathetic nervous system activation) and deep sleep were each statistically significantly correlated with greater RBD antibody responses.

19. **Information theory reveals physiological manifestations of COVID-19 that correlate with symptom density of illness.**
    Front Netw Physiol 2024 · [PMID 38948084](https://pubmed.ncbi.nlm.nih.gov/38948084/) · [DOI 10.3389/fnetp.2024.1211413](https://doi.org/10.3389/fnetp.2024.1211413)

    > We test this framework on five physiological data streams (heart rate, heart rate variability, respiratory rate, metabolic activity, and sleep temperature) assessed at the time of reported illness onset in a previously reported COVID-19-positive cohort (N = 73).

20. **Resting heart rate and the risk of cardiovascular disease, total cancer, and all-cause mortality - A systematic review and dose-response meta-analysis of prospective studies.**
    Nutr Metab Cardiovasc Dis 2017 · [PMID 28552551](https://pubmed.ncbi.nlm.nih.gov/28552551/) · [DOI 10.1016/j.numecd.2017.04.004](https://doi.org/10.1016/j.numecd.2017.04.004)

    > This meta-analysis found an increased risk of coronary heart disease, sudden cardiac death, heart failure, atrial fibrillation, stroke, cardiovascular disease, total cancer and all-cause mortality with greater resting heart rate.

21. **Resting Heart Rate as a Predictor of Cancer Mortality: A Systematic Review and Meta-Analysis.**
    J Clin Med 2021 · [PMID 33806038](https://pubmed.ncbi.nlm.nih.gov/33806038/) · [DOI 10.3390/jcm10071354](https://doi.org/10.3390/jcm10071354)

    > In conclusion, a low RHR is a potential marker of low risk of cancer mortality.

22. **Heart rate variability as a marker of healthy ageing.**
    Int J Cardiol 2018 · [PMID 30104034](https://pubmed.ncbi.nlm.nih.gov/30104034/) · [DOI 10.1016/j.ijcard.2018.08.005](https://doi.org/10.1016/j.ijcard.2018.08.005)

    > Autonomic responding reflected by heart rate variability (HRV) has well-established links to general health and wellbeing in younger populations; but has yet to be explored in older individuals.

23. **Heart rate variability: A biomarker of frailty in older adults?**
    Front Med (Lausanne) 2022 · [PMID 36314012](https://pubmed.ncbi.nlm.nih.gov/36314012/) · [DOI 10.3389/fmed.2022.1008970](https://doi.org/10.3389/fmed.2022.1008970)

    > It contributes to understanding that the changes in heart variability can be a marker for frailty in older adults.

24. **Mobile Heart Rate Variability Biofeedback as a Complementary Intervention After Myocardial Infarction: a Randomized Controlled Study.**
    Int J Behav Med 2021 · [PMID 34008159](https://pubmed.ncbi.nlm.nih.gov/34008159/) · [DOI 10.1007/s12529-021-10000-6](https://doi.org/10.1007/s12529-021-10000-6)

    > HRV-BF as an adjunctive behavioral treatment increased HRV, which is an indicator of lower cardiovascular risk, and self-efficacy, which suggests heightened psychological resilience.

25. **Physical activity, mindfulness meditation, or heart rate variability biofeedback for stress reduction: a randomized controlled trial.**
    Appl Psychophysiol Biofeedback 2015 · [PMID 26111942](https://pubmed.ncbi.nlm.nih.gov/26111942/) · [DOI 10.1007/s10484-015-9293-x](https://doi.org/10.1007/s10484-015-9293-x)

    > Results indicated an overall beneficial effect consisting of reduced stress, anxiety and depressive symptoms, and improved psychological well-being and sleep quality.

26. **Imbalanced sleep increases mortality risk by 14-34%: a meta-analysis.**
    Geroscience 2025 · [PMID 40072785](https://pubmed.ncbi.nlm.nih.gov/40072785/) · [DOI 10.1007/s11357-025-01592-y](https://doi.org/10.1007/s11357-025-01592-y)

    > Short sleep duration (< 7 h per night) was associated with a 14% increase in mortality risk compared to the reference of 7-8 h, with a pooled hazard ratio of 1.14 (95% CI 1.10 to 1.18).

27. **Validation of nocturnal resting heart rate and heart rate variability in consumer wearables.**
    Physiol Rep 2025 · [PMID 40834291](https://pubmed.ncbi.nlm.nih.gov/40834291/) · [DOI 10.14814/phy2.70527](https://doi.org/10.14814/phy2.70527)

    > Oura devices showed the highest agreement for RHR and HRV, and WHOOP showed acceptable agreement, whereas Garmin Fenix and Polar demonstrated lower concordance, highlighting the importance of continuous validation and providing valuable benchmarks for clinicians, researchers, and consumers.

28. **Accuracy of Heart Rate Measurement Under Transient States: A Validation Study of Wearables for Real-Life Monitoring.**
    Sensors (Basel) 2025 · [PMID 41157371](https://pubmed.ncbi.nlm.nih.gov/41157371/) · [DOI 10.3390/s25206319](https://doi.org/10.3390/s25206319)

    > The WHOOP 4.0, Withings Scanwatch, and EmbracePlus devices performed acceptably during steady-state conditions, but were less accurate during transitions.

29. **Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review.**
    JMIR Mhealth Uhealth 2024 · [PMID 38557808](https://pubmed.ncbi.nlm.nih.gov/38557808/) · [DOI 10.2196/52192](https://doi.org/10.2196/52192)

    > WHOOP showed the least disagreement relative to PSG and Sleep Profiler for total sleep time (-1.4 min), light sleep (-9.6 min), and deep sleep (-9.3 min) but showed the largest disagreement for rapid eye movement (REM) sleep (21.0 min).

30. **Performance of consumer wrist-worn sleep tracking devices compared to polysomnography: a meta-analysis.**
    J Clin Sleep Med 2025 · [PMID 39484805](https://pubmed.ncbi.nlm.nih.gov/39484805/) · [DOI 10.5664/jcsm.11460](https://doi.org/10.5664/jcsm.11460)

    > Wrist-worn sleep tracking devices, although popular, are not as reliable as polysomnography in measuring key sleep parameters such as total sleep time, sleep efficiency, and sleep latency.

31. **Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.**
    N Engl J Med 2019 · [PMID 31722151](https://pubmed.ncbi.nlm.nih.gov/31722151/) · [DOI 10.1056/NEJMoa1901183](https://doi.org/10.1056/NEJMoa1901183)

    > Among participants who received notification of an irregular pulse, 34% had atrial fibrillation on subsequent ECG patch readings and 84% of notifications were concordant with atrial fibrillation.

32. **Smartwatch Performance for the Detection and Quantification of Atrial Fibrillation.**
    Circ Arrhythm Electrophysiol 2019 · [PMID 31113234](https://pubmed.ncbi.nlm.nih.gov/31113234/) · [DOI 10.1161/CIRCEP.118.006834](https://doi.org/10.1161/CIRCEP.118.006834)

    > Of these, the SmartRhythm 2.0 neural network detected 80 episodes (episode sensitivity, 97.5%) with a total duration of 1101.1 hours (duration sensitivity, 97.7%).

33. **Clinical Validation of 5 Direct-to-Consumer Wearable Smart Devices to Detect Atrial Fibrillation: BASEL Wearable Study.**
    JACC Clin Electrophysiol 2023 · [PMID 36858690](https://pubmed.ncbi.nlm.nih.gov/36858690/) · [DOI 10.1016/j.jacep.2022.09.011](https://doi.org/10.1016/j.jacep.2022.09.011)

    > Sensitivity and specificity for the detection of AF were comparable between devices: 85% and 75% for the Apple Watch 6, 85% and 75% for the Samsung Galaxy Watch 3, 58% and 75% for the Withings Scanwatch, 66% and 79% for the Fitbit Sense, and 79% and 69% for the AliveCor KardiaMobile, respectively.

34. **Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study.**
    JMIR Form Res 2025 · [PMID 39791483](https://pubmed.ncbi.nlm.nih.gov/39791483/) · [DOI 10.2196/65139](https://doi.org/10.2196/65139)

    > The sensitivity to detect AF was 100% for all devices. The specificity to detect sinus rhythm was 96.4% (95% CI 89.5%-98.8%) for KardiaMobile 6L, 97.8% (95% CI 91.6%-99.5%) for Apple Watch, 98.9% (95% CI 92.5%-99.8%) for FibriCheck, and 97.8% (95% CI 91.5%-99.4%) for Preventicus (P=.50).

35. **Accuracy of the Apple watch for detection of AF: A multicenter experience.**
    J Cardiovasc Electrophysiol 2023 · [PMID 36942773](https://pubmed.ncbi.nlm.nih.gov/36942773/) · [DOI 10.1111/jce.15892](https://doi.org/10.1111/jce.15892)

    > In a population with known AF, the AW IRN had a low rate of false positive detections and high specificity. Sensitivity for detection by subject and by AF episode was lower.

36. **Diagnostic accuracy of apple watch ECG outputs in identifying dysrhythmias: A comparison with 12-Lead ECG in emergency department.**
    Am J Emerg Med 2024 · [PMID 38330880](https://pubmed.ncbi.nlm.nih.gov/38330880/) · [DOI 10.1016/j.ajem.2024.01.046](https://doi.org/10.1016/j.ajem.2024.01.046)

    > Using Bland-Altman analysis for heart rate assessment, the absolute mean difference for heart rate was 0.81 ± 6.12 bpm (r = 0.94). There was strong agreement in 658 out of 700 (94%) heart rate measurements.

37. **A comparison of manual electrocardiographic interval and waveform analysis in lead 1 of 12-lead ECG and Apple Watch ECG: A validation study.**
    Cardiovasc Digit Health J 2020 · [PMID 35265871](https://pubmed.ncbi.nlm.nih.gov/35265871/) · [DOI 10.1016/j.cvdhj.2020.07.002](https://doi.org/10.1016/j.cvdhj.2020.07.002)

    > The AW produces accurate ECGs in healthy adults with moderate to strong agreement of basic ECG intervals.

38. **Use of a Smart Watch for Early Detection of Paroxysmal Atrial Fibrillation: Validation Study.**
    JMIR Cardio 2020 · [PMID 32012044](https://pubmed.ncbi.nlm.nih.gov/32012044/) · [DOI 10.2196/14857](https://doi.org/10.2196/14857)

    > In this validation study, the detection precision of AF and measurement accuracy during AF were both better with Apple Watch W mode than with FBT.

39. **False Atrial Fibrillation Alerts from Smartwatches are Associated with Decreased Perceived Physical Well-being and Confidence in Chronic Symptoms Management.**
    Cardiol Cardiovasc Med 2023 · [PMID 37476150](https://pubmed.ncbi.nlm.nih.gov/37476150/) · [DOI 10.26502/fccm.92920314](https://doi.org/10.26502/fccm.92920314)

    > Receipt of false AF alerts was related to a dose-dependent decline in self-perceived physical health and levels of disease self-management.

40. **Real-World Accuracy of Wearable Activity Trackers for Detecting Medical Conditions: Systematic Review and Meta-Analysis.**
    JMIR Mhealth Uhealth 2024 · [PMID 39213525](https://pubmed.ncbi.nlm.nih.gov/39213525/) · [DOI 10.2196/56972](https://doi.org/10.2196/56972)

    > For atrial fibrillation detection, pooled positive predictive value was 87.4% (95% CI 75.7%-99.1%), sensitivity was 94.2% (95% CI 88.7%-99.7%), and specificity was 95.3% (95% CI 91.8%-98.8%).

41. **Effectiveness of a Smartwatch App in Detecting Induced Falls: Observational Study.**
    JMIR Form Res 2022 · [PMID 35311686](https://pubmed.ncbi.nlm.nih.gov/35311686/) · [DOI 10.2196/30121](https://doi.org/10.2196/30121)

    > The overall smartwatch app sensitivity for falls was 77%, the specificity was 99%, the false-positive rate was 1.7%, and the false-negative rate was 16.4%.

42. **Prospective Associations of Daily Step Counts and Intensity With Cancer and Cardiovascular Disease Incidence and Mortality and All-Cause Mortality.**
    JAMA Intern Med 2022 · [PMID 36094529](https://pubmed.ncbi.nlm.nih.gov/36094529/) · [DOI 10.1001/jamainternmed.2022.4000](https://doi.org/10.1001/jamainternmed.2022.4000)

    > The findings of this population-based prospective cohort study of 78 500 individuals suggest that up to 10 000 steps per day may be associated with a lower risk of mortality and cancer and CVD incidence.

43. **Association of Daily Step Patterns With Mortality in US Adults.**
    JAMA Netw Open 2023 · [PMID 36976556](https://pubmed.ncbi.nlm.nih.gov/36976556/) · [DOI 10.1001/jamanetworkopen.2023.5174](https://doi.org/10.1001/jamanetworkopen.2023.5174)

    > Compared with participants who walked 8000 steps or more 0 days per week, all-cause mortality risk was lower among those who took 8000 steps or more 1 to 2 days per week (aRD, -14.9%; 95% CI -18.8% to -10.9%) and 3 to 7 days per week (aRD, -16.5%; 95% CI, -20.4% to -12.5%).

44. **Association of accelerometer-derived step volume and intensity with hospitalizations and mortality in older adults: A prospective cohort study.**
    J Sport Health Sci 2021 · [PMID 34029758](https://pubmed.ncbi.nlm.nih.gov/34029758/) · [DOI 10.1016/j.jshs.2021.05.004](https://doi.org/10.1016/j.jshs.2021.05.004)

    > Among older adults, both high step volume and step intensity were significantly associated with lower hospitalization and all-cause mortality risk.

45. **Consumer-Based Wearable Activity Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis.**
    JMIR Mhealth Uhealth 2019 · [PMID 30977740](https://pubmed.ncbi.nlm.nih.gov/30977740/) · [DOI 10.2196/11819](https://doi.org/10.2196/11819)

    > Utilizing a consumer-based wearable activity tracker as either the primary component of an intervention or as part of a broader physical activity intervention has the potential to increase physical activity participation.

46. **Wearable Activity Tracker-Based Interventions for Physical Activity, Body Composition, and Physical Function Among Community-Dwelling Older Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials.**
    J Med Internet Res 2025 · [PMID 40179387](https://pubmed.ncbi.nlm.nih.gov/40179387/) · [DOI 10.2196/59507](https://doi.org/10.2196/59507)

    > Compared to usual care, there was lo- to moderate-certainty evidence that the wearable activity tracker-based interventions significantly increased physical activity time (standardized mean difference [SMD]=0.28, 95% CI 0.10-0.47; P=.003) and daily step counts (SMD=0.58, 95% CI 0.33-0.83; P<.001) immediately after intervention

47. **The association between daily step count and all-cause and cardiovascular mortality: a meta-analysis.**
    Eur J Prev Cardiol 2023 · [PMID 37555441](https://pubmed.ncbi.nlm.nih.gov/37555441/) · [DOI 10.1093/eurjpc/zwad229](https://doi.org/10.1093/eurjpc/zwad229)

    > A 1000-step increment was associated with a 15% decreased risk of all-cause mortality [hazard ratio (HR) 0.85; 95% confidence interval (CI) 0.81-0.91; P < 0.001], while a 500-step increment was associated with a 7% decrease in CV mortality (HR 0.93; 95% CI 0.91-0.95; P < 0.001).

48. **Daily steps and all-cause mortality: An umbrella review and meta-analysis.**
    Prev Med 2024 · [PMID 38901742](https://pubmed.ncbi.nlm.nih.gov/38901742/) · [DOI 10.1016/j.ypmed.2024.108047](https://doi.org/10.1016/j.ypmed.2024.108047)

    > Our updated meta-analysis showed a nonlinear association, indicating a lower risk of all-cause mortality with increased daily steps, with a protective threshold at 3143 steps/day, and a pooled HR of 0.91 (95% CI: 0.87, 0.95) per 1000 steps/day increment.

49. **Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis.**
    BMJ 2019 · [PMID 31434697](https://pubmed.ncbi.nlm.nih.gov/31434697/) · [DOI 10.1136/bmj.l4570](https://doi.org/10.1136/bmj.l4570)

    > Higher levels of total physical activity, at any intensity, and less time spent sedentary, are associated with substantially reduced risk for premature mortality, with evidence of a non-linear dose-response pattern in middle aged and older adults.

50. **Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes: a systematic review and dose response meta-analysis.**
    Eur J Epidemiol 2018 · [PMID 29589226](https://pubmed.ncbi.nlm.nih.gov/29589226/) · [DOI 10.1007/s10654-018-0380-1](https://doi.org/10.1007/s10654-018-0380-1)

    > Independent of PA, total sitting and TV viewing time are associated with greater risk for several major chronic disease outcomes.

51. **Survival of the fittest: VOmax, a key predictor of longevity?**
    Front Biosci (Landmark Ed) 2018 · [PMID 29293447](https://pubmed.ncbi.nlm.nih.gov/29293447/) · [DOI 10.2741/4657](https://doi.org/10.2741/4657)

    > Cardiorespiratory fitness, as measured by maximal oxygen uptake (VOmax), is related to functional capacity and human performance and has been shown to be a strong and independent predictor of all-cause and disease-specific mortality.

52. **Impact of Cardiorespiratory Fitness on All-Cause and Disease-Specific Mortality**
    Prog Cardiovasc Dis 2017 · [PMID 28286137](https://pubmed.ncbi.nlm.nih.gov/28286137/) · [DOI 10.1016/j.pcad.2017.03.001](https://doi.org/10.1016/j.pcad.2017.03.001)

    > Cardiorespiratory fitness is a strong, independent predictor of all-cause and disease-specific mortality

53. **Health Benefits of Different Sports: a Systematic Review and Meta-Analysis of Longitudinal and Intervention Studies Including 2.6 Million Adult Participants.**
    Sports Med Open 2024 · [PMID 38658416](https://pubmed.ncbi.nlm.nih.gov/38658416/) · [DOI 10.1186/s40798-024-00692-x](https://doi.org/10.1186/s40798-024-00692-x)

    > A range of physical health benefits are associated with participation in recreational cycling, football, handball, running and swimming.

54. **Daily Step Count and All-Cause Mortality: A Dose-Response Meta-analysis of Prospective Cohort Studies.**
    Sports Med 2021 · [PMID 34417979](https://pubmed.ncbi.nlm.nih.gov/34417979/) · [DOI 10.1007/s40279-021-01536-4](https://doi.org/10.1007/s40279-021-01536-4)

    > Dose-response meta-analysis indicated a strong inverse association, wherein the risk decreased linearly from 2700 to17,000 steps per day. The HR for 10,000 steps per day was 0.44 (95% CI 0.31-0.63).

55. **The relationships between step count and all-cause mortality and cardiovascular events: A dose-response meta-analysis.**
    J Sport Health Sci 2021 · [PMID 34547483](https://pubmed.ncbi.nlm.nih.gov/34547483/) · [DOI 10.1016/j.jshs.2021.09.004](https://doi.org/10.1016/j.jshs.2021.09.004)

    > Our meta-analysis suggests inverse associations between higher step count and risk of premature death and cardiovascular events in middle-aged and older adults, with nonlinear dose-response patterns.

56. **Walking and Health Outcomes in Older Adults: A Systematic Review and Meta-Analysis of Longitudinal Studies.**
    Am J Health Promot 2026 · [PMID 42117327](https://pubmed.ncbi.nlm.nih.gov/42117327/) · [DOI 10.1177/08901171261438402](https://doi.org/10.1177/08901171261438402)

    > Older adults who performed an average of 5694 steps/day, had a 13% lower risk of all-cause mortality (HR: 0.87, 0.80-0.95) per additional 1000 steps/day.

57. **Midlife Cardiorespiratory Fitness and the Long-Term Risk of Mortality: 46 Years of Follow-Up.**
    J Am Coll Cardiol 2018 · [PMID 30139444](https://pubmed.ncbi.nlm.nih.gov/30139444/) · [DOI 10.1016/j.jacc.2018.06.045](https://doi.org/10.1016/j.jacc.2018.06.045)

    > Each unit increase in Vomax was associated with a 45-day (95% CI: 30 to 61; p < 0.001) increase in longevity.

58. **Long-term Change in Cardiorespiratory Fitness and All-Cause Mortality: A Population-Based Study**
    Mayo Clin Proc 2016 · [PMID 27444976](https://pubmed.ncbi.nlm.nih.gov/27444976/) · [DOI 10.1016/j.mayocp.2016.05.014](https://doi.org/10.1016/j.mayocp.2016.05.014)

    > a higher change in VO2max was associated with a 9% relative risk reduction of all-cause mortality

59. **The Effect of Physical Activity and Cardiorespiratory Fitness on All-Cause Mortality in Hong Kong Chinese Older Adults.**
    J Gerontol A Biol Sci Med Sci 2018 · [PMID 29029009](https://pubmed.ncbi.nlm.nih.gov/29029009/) · [DOI 10.1093/gerona/glx180](https://doi.org/10.1093/gerona/glx180)

    > As compared with those being active and fit, physically inactive and cardiorespiratory unfit individuals had the highest all-cause mortality risk.

60. **Effects of Activity Tracker Use With Health Professional Support or Telephone Counseling on Maintenance of Physical Activity and Health Outcomes in Older Adults: Randomized Controlled Trial.**
    JMIR Mhealth Uhealth 2021 · [PMID 33399541](https://pubmed.ncbi.nlm.nih.gov/33399541/) · [DOI 10.2196/18686](https://doi.org/10.2196/18686)

    > The use of an AT with AEP support or TC is effective at maintaining daily step count in older adults over a 12-month period, suggesting that wearable ATs are as effective as TC.

61. **The Impact of a Wearable Activity Tracker and Structured Feedback Program on Physical Activity in Hemodialysis Patients: The Step4Life Pilot Randomized Controlled Trial.**
    Am J Kidney Dis 2023 · [PMID 36801430](https://pubmed.ncbi.nlm.nih.gov/36801430/) · [DOI 10.1053/j.ajkd.2022.12.011](https://doi.org/10.1053/j.ajkd.2022.12.011)

    > This pilot randomized controlled trial demonstrated that structured feedback coupled with a wearable activity tracker led to a greater daily step count that was sustained over 12 weeks relative to a wearable activity tracker alone.

62. **Impact of a Wearable Activity Tracker on Disease Flares in Spondyloarthritis: A Randomized Controlled Trial.**
    J Rheumatol 2022 · [PMID 35705234](https://pubmed.ncbi.nlm.nih.gov/35705234/) · [DOI 10.3899/jrheum.220140](https://doi.org/10.3899/jrheum.220140)

    > The use of a wearable activity tracker did not affect the number of flares, performance, or QOL of patients with SpA.

63. **Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort.**
    J Pers Med 2017 · [PMID 28538708](https://pubmed.ncbi.nlm.nih.gov/28538708/) · [DOI 10.3390/jpm7020003](https://doi.org/10.3390/jpm7020003)

    > Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent.

64. **Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study.**
    JMIR Mhealth Uhealth 2019 · [PMID 30855232](https://pubmed.ncbi.nlm.nih.gov/30855232/) · [DOI 10.2196/10828](https://doi.org/10.2196/10828)

    > The Apple Watch 3 and the Fitbit Charge 2 provided acceptable heart rate accuracy (<±10%) across the 24 hour and during each activity, except for the Apple Watch 3 during the daily activities condition.

65. **Stressing the accuracy: Wrist-worn wearable sensor validation over different conditions.**
    Psychophysiology 2019 · [PMID 31332802](https://pubmed.ncbi.nlm.nih.gov/31332802/) · [DOI 10.1111/psyp.13441](https://doi.org/10.1111/psyp.13441)

    > Mean HR measures showed the best accuracy over all conditions. HRV measures showed satisfactory accuracy in seated rest, paced breathing, and recovery conditions but not in dynamic conditions, including speaking.

66. **Performance of seven consumer sleep-tracking devices compared with polysomnography.**
    Sleep 2021 · [PMID 33378539](https://pubmed.ncbi.nlm.nih.gov/33378539/) · [DOI 10.1093/sleep/zsaa291](https://doi.org/10.1093/sleep/zsaa291)

    > Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent.

67. **Atrial fibrillation detection using ambulatory smartwatch photoplethysmography and validation with simultaneous holter recording.**
    Am Heart J 2022 · [PMID 35131229](https://pubmed.ncbi.nlm.nih.gov/35131229/) · [DOI 10.1016/j.ahj.2022.02.002](https://doi.org/10.1016/j.ahj.2022.02.002)

    > Among the 200 available participants, 112 participants (56%) developed AF (the AF group). The sensitivity, specificity, and positive predicted value of AF detection in participants were 97.3%, 88.6%, and 91.6%, respectively.

68. **Diagnostic accuracy of smart gadgets/wearable devices in detecting atrial fibrillation: A systematic review and meta-analysis.**
    Arch Cardiovasc Dis 2020 · [PMID 32921618](https://pubmed.ncbi.nlm.nih.gov/32921618/) · [DOI 10.1016/j.acvd.2020.05.015](https://doi.org/10.1016/j.acvd.2020.05.015)

    > Smartphones had a sensitivity of 94% and a specificity of 96%, and smartwatches showed similar diagnostic accuracy, with a specificity of 94% and a sensitivity of 93%.

69. **Sedentary behavior patterns and the risk of non-communicable diseases and all-cause mortality: A systematic review and meta-analysis.**
    Int J Nurs Stud 2023 · [PMID 37523952](https://pubmed.ncbi.nlm.nih.gov/37523952/) · [DOI 10.1016/j.ijnurstu.2023.104563](https://doi.org/10.1016/j.ijnurstu.2023.104563)

    > A prolonged sedentary behavior pattern was associated with increased risks of several major noncommunicable diseases and all-cause mortality.

70. **Effectiveness of Wearable Trackers on Physical Activity in Healthy Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials.**
    JMIR Mhealth Uhealth 2020 · [PMID 32706685](https://pubmed.ncbi.nlm.nih.gov/32706685/) · [DOI 10.2196/15576](https://doi.org/10.2196/15576)

    > The usage of wearable trackers was associated with increased physical activity (standardized mean difference 0.449, 95% CI 0.10-0.80; P=.01). In the subgroup analyses, however, wearable trackers demonstrated no clear benefit for physical activity or weight reduction.

71. **Effects of Integrating Wearable Activity Trackers With a Home-Based Multicomponent Exercise Intervention on Fall-Related Parameters and Physical Function in Older Adults: Randomized Controlled Trial.**
    JMIR Mhealth Uhealth 2025 · [PMID 40340847](https://pubmed.ncbi.nlm.nih.gov/40340847/) · [DOI 10.2196/64458](https://doi.org/10.2196/64458)

    > Wearable technology, with or without an exercise intervention, seems to be an effective tool in reducing the fear of falling and improving physical function in older adults susceptible to falls.

72. **Effect of a Wearable Device-Based Physical Activity Intervention in North Korean Refugees: Pilot Randomized Controlled Trial.**
    J Med Internet Res 2023 · [PMID 37467013](https://pubmed.ncbi.nlm.nih.gov/37467013/) · [DOI 10.2196/45975](https://doi.org/10.2196/45975)

    > The wearable device-based physical activity intervention did not significantly increase the average daily step count in the North Korean refugees in this study.

73. **Health wearable devices for weight and BMI reduction in individuals with overweight/obesity and chronic comorbidities: systematic review and network meta-analysis.**
    Br J Sports Med 2021 · [PMID 33731385](https://pubmed.ncbi.nlm.nih.gov/33731385/) · [DOI 10.1136/bjsports-2020-103594](https://doi.org/10.1136/bjsports-2020-103594)

    > Health wearable devices are effective intervention tools/strategies for reducing body weight and BMI in individuals with overweight/obesity and chronic comorbidities.

74. **Long-Term Weight Management Using Wearable Technology in Overweight and Obese Adults: Systematic Review.**
    JMIR Mhealth Uhealth 2020 · [PMID 32154788](https://pubmed.ncbi.nlm.nih.gov/32154788/) · [DOI 10.2196/13461](https://doi.org/10.2196/13461)

    > This review showed some evidence that wearable devices can improve long-term physical activity and weight loss outcomes, but there was not enough evidence to show a benefit over the comparator methods.

75. **Systematic Review of Fitbit Charge 2 Validation Studies for Exercise Tracking.**
    Transl J Am Coll Sports Med 2022 · [PMID 36711436](https://pubmed.ncbi.nlm.nih.gov/36711436/) · [DOI 10.1249/tjx.0000000000000215](https://doi.org/10.1249/tjx.0000000000000215)

    > The literature supports the validity of the FBC2 to accurately monitor HR, but for step count is inconclusive so the device may not be suitable for recommended use in all populations.

76. **Detection of sedentary time and bouts using consumer-grade wrist-worn devices: a hidden semi-Markov model.**
    BMC Med Res Methodol 2024 · [PMID 39350114](https://pubmed.ncbi.nlm.nih.gov/39350114/) · [DOI 10.1186/s12874-024-02311-5](https://doi.org/10.1186/s12874-024-02311-5)

    > STEPHEN can characterize the proportion of time spent being sedentary and usual sedentary bout length.

77. **Relationship of resting heart rate and blood pressure with all-cause and cardiovascular disease mortality.**
    Public Health 2022 · [PMID 35728416](https://pubmed.ncbi.nlm.nih.gov/35728416/) · [DOI 10.1016/j.puhe.2022.03.020](https://doi.org/10.1016/j.puhe.2022.03.020)

    > The risk of all-cause mortality was increased by 25% with the quartiles four vs quartile one of RHR (HR [95% CI]:1.25 [1.17-1.33]), and CVD mortality was increased by 32% (HR [95% CI]: 1.32 [1.22-1.44]).

78. **Detection of Atrial Fibrillation in a Large Population Using Wearable Devices: The Fitbit Heart Study.**
    Circulation 2022 · [PMID 36148649](https://pubmed.ncbi.nlm.nih.gov/36148649/) · [DOI 10.1161/CIRCULATIONAHA.122.060291](https://doi.org/10.1161/CIRCULATIONAHA.122.060291)

    > Of the 225 participants with another IHRD during ECG patch monitoring, 221 had concurrent AF on the ECG and 4 did not, resulting in an IHRD positive predictive value of 98.2% (95% CI, 95.5%-99.5%).

79. **Diagnostic Accuracy of Smartwatches for the Detection of Cardiac Arrhythmia: Systematic Review and Meta-analysis.**
    J Med Internet Res 2021 · [PMID 34448706](https://pubmed.ncbi.nlm.nih.gov/34448706/) · [DOI 10.2196/28974](https://doi.org/10.2196/28974)

    > The overall sensitivity, specificity, and accuracy of smartwatches for detecting cardiac arrhythmias were 100% (95% CI 0.99-1.00), 95% (95% CI 0.93-0.97), and 97% (95% CI 0.96-0.99), respectively.

80. **Single-lead electrocardiogram Artificial Intelligence model with risk factors detects atrial fibrillation during sinus rhythm.**
    Europace 2024 · [PMID 38079535](https://pubmed.ncbi.nlm.nih.gov/38079535/) · [DOI 10.1093/europace/euad354](https://doi.org/10.1093/europace/euad354)

    > An AI model using a single-lead SR ECG and six risk factors can identify patients with concurrent AF with similar accuracy as a 12-lead ECG-AI model.

81. **Smartwatch Based Atrial Fibrillation Detection from Photoplethysmography Signals.**
    Annu Int Conf IEEE Eng Med Biol Soc 2019 · [PMID 31946820](https://pubmed.ncbi.nlm.nih.gov/31946820/) · [DOI 10.1109/EMBC.2019.8856928](https://doi.org/10.1109/EMBC.2019.8856928)

    > Our method achieves sensitivity, specificity and accuracy of 96.15%, 97.37% and 97.11%, respectively, which shows the potential of a practical and reliable AF monitoring scheme.

82. **Electrodermal Activity Based Pre-surgery Stress Detection Using a Wrist Wearable.**
    IEEE J Biomed Health Inform 2019 · [PMID 30668508](https://pubmed.ncbi.nlm.nih.gov/30668508/) · [DOI 10.1109/JBHI.2019.2893222](https://doi.org/10.1109/JBHI.2019.2893222)

    > The scheme yielded a classification accuracy of 85.06% on a new user dataset and proved to be more effective than the general supervised classification model.

83. **Wearables measuring electrodermal activity to assess perceived stress in care: a scoping review.**
    Acta Neuropsychiatr 2023 · [PMID 36960675](https://pubmed.ncbi.nlm.nih.gov/36960675/) · [DOI 10.1017/neu.2023.19](https://doi.org/10.1017/neu.2023.19)

    > Wearable EDA sensors are promising in detecting perceived stress. Field studies with relevant populations in a health or care context are lacking.

84. **Examining Stress and Residual Symptoms in Remitted and Partially Remitted Depression Using a Wearable Electrodermal Activity Device: A Pilot Study.**
    IEEE J Transl Eng Health Med 2022 · [PMID 36644642](https://pubmed.ncbi.nlm.nih.gov/36644642/) · [DOI 10.1109/JTEHM.2022.3228483](https://doi.org/10.1109/JTEHM.2022.3228483)

    > Increased residual symptoms were associated with enhanced self-reported stress on the same day. Increased SCRs on one day predicted increased residual symptoms on the next day.

85. **Perceived job insecurity as a risk factor for incident coronary heart disease: systematic review and meta-analysis.**
    BMJ 2013 · [PMID 23929894](https://pubmed.ncbi.nlm.nih.gov/23929894/) · [DOI 10.1136/bmj.f4746](https://doi.org/10.1136/bmj.f4746)

    > Age adjusted relative risk of high versus low job insecurity was 1.32 (95% confidence interval 1.09 to 1.59).

86. **Meta-analysis of perceived stress and its association with incident coronary heart disease.**
    Am J Cardiol 2012 · [PMID 22975465](https://pubmed.ncbi.nlm.nih.gov/22975465/) · [DOI 10.1016/j.amjcard.2012.08.004](https://doi.org/10.1016/j.amjcard.2012.08.004)

    > Meta-analysis yielded an aggregate risk ratio of 1.27 (95% confidence interval 1.12 to 1.45) for the magnitude of the relation between high perceived stress and incident CHD.

87. **Validation of the Withings ScanWatch as a Wrist-Worn Reflective Pulse Oximeter: Prospective Interventional Clinical Study.**
    J Med Internet Res 2021 · [PMID 33857011](https://pubmed.ncbi.nlm.nih.gov/33857011/) · [DOI 10.2196/27503](https://doi.org/10.2196/27503)

    > We found a strong association and a high level of agreement between the measurements collected from the devices, with high Pearson correlation coefficients of r=0.944 and r=0.954 on the correlation plots.

88. **Multidimensional Circadian Monitoring by Wearable Biosensors in Parkinson's Disease.**
    Front Neurol 2018 · [PMID 29632508](https://pubmed.ncbi.nlm.nih.gov/29632508/) · [DOI 10.3389/fneur.2018.00157](https://doi.org/10.3389/fneur.2018.00157)

    > Our study demonstrates that a multichannel ACM device collects reliable and complementary information from motor (acceleration and time in movement) and common non-motor (sleep and skin temperature rhythms) features frequently disrupted in PD.

89. **Heart rate variability in the prediction of mortality: A systematic review and meta-analysis of healthy and patient populations.**
    Neurosci Biobehav Rev 2022 · [PMID 36243195](https://pubmed.ncbi.nlm.nih.gov/36243195/) · [DOI 10.1016/j.neubiorev.2022.104907](https://doi.org/10.1016/j.neubiorev.2022.104907)

    > Lower HRV parameter values were significant predictors of higher mortality across different ages, sex, continents, populations and recording lengths.

90. **Heart rate as a target of treatment of chronic heart failure.**
    J Cardiol 2012 · [PMID 22920717](https://pubmed.ncbi.nlm.nih.gov/22920717/) · [DOI 10.1016/j.jjcc.2012.06.013](https://doi.org/10.1016/j.jjcc.2012.06.013)

    > In a long-term follow-up study in Framingham, the general population in this cohort showed an increase in all-cause mortality by 14% at every 10 bpm increase in HR.

91. **Wrist-worn devices for the measurement of heart rate and energy expenditure: A validation study for the Apple Watch 6, Polar Vantage V and Fitbit Sense.**
    Eur J Sport Sci 2022 · [PMID 34957939](https://pubmed.ncbi.nlm.nih.gov/34957939/) · [DOI 10.1080/17461391.2021.2023656](https://doi.org/10.1080/17461391.2021.2023656)

    > The Apple Watch 6 was the most accurate for measuring heart rate, whereas the Polar Vantage V and Fitbit Sense showed variable results dependent on the activity

92. **Accuracy of the Multisensory Wristwatch Polar Vantage's Estimation of Energy Expenditure in Various Activities: Instrument Validation Study.**
    JMIR Mhealth Uhealth 2019 · [PMID 31579020](https://pubmed.ncbi.nlm.nih.gov/31579020/) · [DOI 10.2196/14534](https://doi.org/10.2196/14534)

    > The Polar Vantage has a statistically moderate-to-good accuracy in EE estimation that is activity dependent.

93. **Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study.**
    Am Heart J 2018 · [PMID 30392584](https://pubmed.ncbi.nlm.nih.gov/30392584/) · [DOI 10.1016/j.ahj.2018.09.002](https://doi.org/10.1016/j.ahj.2018.09.002)

    > Smartwatch and fitness band wearable consumer electronics can passively measure pulse rate from the wrist using photoplethysmography (PPG). Identification of pulse irregularity or variability from these data has the potential to identify atrial fibrillation or atrial flutter (AF, collectively).

94. **Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses.**
    The Lancet. Digital health 2022 · [PMID 35868813](https://pubmed.ncbi.nlm.nih.gov/35868813/)

    > Umbrella review of 39 meta-analyses (163,992 participants): trackers add roughly 1,800 steps/day and 40 min/day of walking with about 1 kg weight loss — enough for the authors to recommend them.

95. **A Validation of Six Wearable Devices for Estimating Sleep, Heart Rate and Heart Rate Variability in Healthy Adults.**
    Sensors (Basel, Switzerland) 2022 · [PMID 36016077](https://pubmed.ncbi.nlm.nih.gov/36016077/)

    > Six-device lab validation against polysomnography/ECG: Oura and WHOOP were the strongest for sleep and HR/HRV, but multi-stage sleep classification reached only about 50-64% agreement across devices.

96. **Apple watch accuracy in monitoring health metrics: a systematic review and meta-analysis.**
    Physiological measurement 2025 · [PMID 40199339](https://pubmed.ncbi.nlm.nih.gov/40199339/)

    > 56-study meta-analysis: Apple Watch heart rate is accurate (mean bias -0.12 bpm) and step counts acceptable, but energy-expenditure estimates failed validity thresholds in every subgroup.

97. **A validation study of the WHOOP strap against polysomnography to assess sleep.**
    Journal of sports sciences 2020 · [PMID 32713257](https://pubmed.ncbi.nlm.nih.gov/32713257/)

    > WHOOP agreed with polysomnography on 89% of epochs for sleep vs. wake (95% sleep sensitivity) and overestimated total sleep time by only about 8 minutes.

98. **Accuracy of the wearable activity tracker Garmin Forerunner 235 for the assessment of heart rate during rest and activity.**
    Journal of sports sciences 2019 · [PMID 30326780](https://pubmed.ncbi.nlm.nih.gov/30326780/)

    > Garmin wrist heart rate was accurate at rest (r=0.997) and during running (r 0.85-0.91) but degraded during low-intensity cycling (r about 0.27-0.46).

99. **Usability and Accuracy of a Smartwatch for the Assessment of Physical Activity in the Elderly Population: Observational Study.**
    JMIR mHealth and uHealth 2021 · [PMID 33949953](https://pubmed.ncbi.nlm.nih.gov/33949953/)

    > Garmin vívoactive step counts matched hand-tallied counts almost perfectly (ICC 0.98) in adults aged 70-90 during real-life walks.

100. **The Sleep of the Ring: Comparison of the ŌURA Sleep Tracker Against Polysomnography.**
     Behavioral sleep medicine 2019 · [PMID 28323455](https://pubmed.ncbi.nlm.nih.gov/28323455/)

     > Early Oura validation (n=41): 96% sensitivity for detecting sleep but only 48% specificity for wake, with REM overestimated by about 17 minutes — staging has improved with newer algorithms.

101. **Wearable activity trackers for promoting physical activity: A systematic meta-analytic review.**
     International journal of medical informatics 2021 · [PMID 34020170](https://pubmed.ncbi.nlm.nih.gov/34020170/)

     > 44-trial review: trackers increase daily steps and weekly moderate-to-vigorous activity but do not reduce sedentary time; effects are larger with professional support.

102. **Heart Rate Variability-Guided Training for Enhancing Cardiac-Vagal Modulation, Aerobic Fitness, and Endurance Performance: A Methodological Systematic Review with Meta-Analysis.**
     International journal of environmental research and public health 2021 · [PMID 34639599](https://pubmed.ncbi.nlm.nih.gov/34639599/)

     > Meta-analysis: adjusting training by morning HRV improved vagal HRV indices more than fixed plans (SMD 0.50), but VO2max and performance advantages were small and not significant.

103. **Interventions Using Wearable Activity Trackers to Improve Patient Physical Activity and Other Outcomes in Adults Who Are Hospitalized: A Systematic Review and Meta-analysis.**
     JAMA network open 2023 · [PMID 37318806](https://pubmed.ncbi.nlm.nih.gov/37318806/)

     > Across 15 studies (n=1,911), wearable-tracker interventions significantly increased objectively measured physical activity in hospitalized and rehabilitation patients.

104. **Association of Cardiorespiratory Fitness With Long-term Mortality Among Adults Undergoing Exercise Treadmill Testing.**
     JAMA network open 2018 · [PMID 30646252](https://pubmed.ncbi.nlm.nih.gov/30646252/)

     > In 122,007 adults (1.1 million person-years), mortality fell monotonically with cardiorespiratory fitness — elite vs. low fitness HR 0.20, with no upper limit of benefit observed.

## Where to buy

[Search Amazon for Garmin Forerunner 265](https://www.amazon.com/s?k=Garmin%20Forerunner%20265&tag=magellanlong-20) — affiliate search link.

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## Scope and disclosures

Educational information, not medical advice. Nothing here is intended to diagnose, treat, cure, or prevent any disease. Talk to your physician before starting any supplement or device, especially if you are pregnant, nursing, or taking medication.

Editorial firewall: evidence grades are assigned from the published research and are independent of any affiliate commission. As an Amazon Associate, Magellan Longevity earns from qualifying purchases.

Reviewed for accuracy by a board-certified physician (DO).