Journal: Frontiers in Physiology

Article Title: Validity of smartwatch-derived estimates of lactate threshold heart rate and pace compared to graded exercise testing

doi: 10.3389/fphys.2025.1621996

Figure Lengend Snippet: Distribution analysis of participant age (A1–C1) , LT HR (A2–C2) , and LT Pace (A3–C3) in the tests of different smartwatches. (A1–A3) represent data from Huawei watches, (B1–B3) from Garmin watches, and (C1–C3) from COROS watches. Each plot displays histogram distributions for test success (blue) and test failure (red), with overlaid density curves and count annotations for each bin.

Article Snippet: This study evaluates the validity of three mainstream smartwatches (Huawei GT Runner®, Garmin Forerunner 265® or 265s®, and Coros Pace3®) in estimating lactate threshold heart rate (LT HR) and pace (LT Pace), comparing these to measurement protocols and results from the modified Dmax method in laboratory standards.

Techniques:

Journal: Frontiers in Physiology

Article Title: Validity of smartwatch-derived estimates of lactate threshold heart rate and pace compared to graded exercise testing

doi: 10.3389/fphys.2025.1621996

Figure Lengend Snippet: Regression analysis comparing LT HR (A1–C1) and LT Pace (A2–C2) measured by smartwatches with those calculated using the DmaxMod method. (A1,A2) represent data from Huawei watches, (B1,B2) from Garmin watches, and (C1,C2) from COROS watches. Each plot includes the fitted regression line, 95% confidence interval (dark red band), and 95% prediction band (light red band), with green dots representing individual data points.

Article Snippet: This study evaluates the validity of three mainstream smartwatches (Huawei GT Runner®, Garmin Forerunner 265® or 265s®, and Coros Pace3®) in estimating lactate threshold heart rate (LT HR) and pace (LT Pace), comparing these to measurement protocols and results from the modified Dmax method in laboratory standards.

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Limited Interchangeability of Smartwatches and Lace-Mounted IMUs for Running Gait Analysis

doi: 10.3390/s25175553

Figure Lengend Snippet: Equivalency plots for the overall cohort for average cadence ( a ), peak cadence ( b ), stride length ( c ), and ground contact time ( d ) for lace-mounted IMUs compared to smartwatch measurement. Equivalence window for equivalence plots determined based on 10% of criterion mean (±5%).

Article Snippet: Some studies suggest smartwatches can detect variability in gait patterns but have demonstrated mixed error and agreement statistics when estimating SL during gait using Garmin, Apple and Samsung smartwatch devices (RSME = 5.29 cm; MAE = 0.13 m; ICC = 0.60) [ , , ].

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Limited Interchangeability of Smartwatches and Lace-Mounted IMUs for Running Gait Analysis

doi: 10.3390/s25175553

Figure Lengend Snippet: Equivalency plots, stratified by males ( a – d ) and females ( e – h ) for average cadence ( a , e ), peak cadence ( b , f ), stride length ( c , g ), and ground contact time ( d , h ) for lace-mounted IMUs compared to smartwatch measurement. Equivalence window for equivalence plots determined based on 10% of criterion mean (±5%).

Article Snippet: Some studies suggest smartwatches can detect variability in gait patterns but have demonstrated mixed error and agreement statistics when estimating SL during gait using Garmin, Apple and Samsung smartwatch devices (RSME = 5.29 cm; MAE = 0.13 m; ICC = 0.60) [ , , ].

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Limited Interchangeability of Smartwatches and Lace-Mounted IMUs for Running Gait Analysis

doi: 10.3390/s25175553

Figure Lengend Snippet: Equivalency plots, stratified by indoor ( a – d ) and outdoor ( e – h ) trials for average cadence ( a , e ), peak cadence ( b , f ), stride length ( c , g ), and ground contact time ( d , h ) for lace-mounted IMUs compared to smartwatch measurement. Equivalence window for equivalence plots determined based on 10% of criterion mean (±5%).

Article Snippet: Some studies suggest smartwatches can detect variability in gait patterns but have demonstrated mixed error and agreement statistics when estimating SL during gait using Garmin, Apple and Samsung smartwatch devices (RSME = 5.29 cm; MAE = 0.13 m; ICC = 0.60) [ , , ].

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Limited Interchangeability of Smartwatches and Lace-Mounted IMUs for Running Gait Analysis

doi: 10.3390/s25175553

Figure Lengend Snippet: Equivalency plots, stratified by short (2.5 km and 5 km); ( a – d ) and long (10 km and 20) km; ( e – h ) distance trials for average cadence ( a , e ), peak cadence ( b , f ), stride length ( c , g ), and ground contact time ( d , h ) for lace-mounted IMUs compared to smartwatch measurement. Equivalence window for equivalence plots determined based on 10% of criterion mean (±5%).

Article Snippet: Some studies suggest smartwatches can detect variability in gait patterns but have demonstrated mixed error and agreement statistics when estimating SL during gait using Garmin, Apple and Samsung smartwatch devices (RSME = 5.29 cm; MAE = 0.13 m; ICC = 0.60) [ , , ].

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Limited Interchangeability of Smartwatches and Lace-Mounted IMUs for Running Gait Analysis

doi: 10.3390/s25175553

Figure Lengend Snippet: Equivalency plots, stratified by height (<166 cm ( a – d ); 166–175 cm ( e – h ); >175 cm ( i – l )) for average cadence ( a , e , i ), peak cadence ( b , f , j ), stride length ( c , g , k ), and ground contact time ( d , h , l ) for lace-mounted IMUs compared to smartwatch measurement. Equivalence window for equivalence plots determined based on 10% of criterion mean (±5%).

Article Snippet: Some studies suggest smartwatches can detect variability in gait patterns but have demonstrated mixed error and agreement statistics when estimating SL during gait using Garmin, Apple and Samsung smartwatch devices (RSME = 5.29 cm; MAE = 0.13 m; ICC = 0.60) [ , , ].

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Limited Interchangeability of Smartwatches and Lace-Mounted IMUs for Running Gait Analysis

doi: 10.3390/s25175553

Figure Lengend Snippet: Equivalency plots, stratified by weight (<60 kg ( a – d ); 60–70 kg ( e – h ); 70–80 kg ( i – l ); 80–90 kg ( m – p ); >90 kg ( q – t ) for average cadence ( a , e , i , m , q ), peak cadence ( b , f , j , n , r ), stride length ( c , g , k , o , s ), and ground contact time ( d , h , l , p , t ) for lace-mounted IMUs compared to smartwatch measurement. Equivalence window for equivalence plots determined based on 10% of criterion mean (±5%).

Article Snippet: Some studies suggest smartwatches can detect variability in gait patterns but have demonstrated mixed error and agreement statistics when estimating SL during gait using Garmin, Apple and Samsung smartwatch devices (RSME = 5.29 cm; MAE = 0.13 m; ICC = 0.60) [ , , ].

Techniques:

Journal: Journal of Sleep Research

Article Title: Evaluation of the Agreement Between Research‐Grade Actigraphy Sleep, Consumer‐Grade Smartwatches and Self‐Reported Sleep Diaries in Masters Endurance Athletes

doi: 10.1111/jsr.70177

Figure Lengend Snippet: Method comparison of total sleep time evaluated using Bland–Altman plots for data from ActiGraph (ACTI), smartwatch (SMART), and self‐reported (SELF) data in male and female masters endurance athletes. * p < 0.05 for the linear regression analysis indicating the presence of proportional bias.

Article Snippet: When examining whether the model tier (high‐end, mid‐range, or low‐end) of Garmin smartwatch influenced agreement between ACTI and SELF, there were no significant differences in TST or SE% values across tiers when compared to ACTI (Table ).

Techniques: Comparison

Journal: Journal of Sleep Research

Article Title: Evaluation of the Agreement Between Research‐Grade Actigraphy Sleep, Consumer‐Grade Smartwatches and Self‐Reported Sleep Diaries in Masters Endurance Athletes

doi: 10.1111/jsr.70177

Figure Lengend Snippet: Agreement analysis of sleep efficiency (SE%) evaluated using Bland–Altman plots for data from ActiGraph (ACTI), smartwatch (SMART), and self‐reported (SELF) data in male and female masters endurance athletes. * p < 0.05 for the linear regression analysis indicating the presence of proportional bias.

Article Snippet: When examining whether the model tier (high‐end, mid‐range, or low‐end) of Garmin smartwatch influenced agreement between ACTI and SELF, there were no significant differences in TST or SE% values across tiers when compared to ACTI (Table ).

Techniques:

Journal: medRxiv

Article Title: Hidden in the Night: Wearable Sleep Assessment of Nocturnal Hypoglycaemia in Type 1 Diabetes

doi: 10.64898/2026.01.22.26344161

Figure Lengend Snippet: Structure of the dataset combining continuous glucose monitoring (CGM) metrics with smartwatch-derived sleep data, including physiological biomarkers, stage-level information, and summary sleep features.

Article Snippet: As the study relied on wearable-derived staging rather than polysomnography, the state of the art in sleep studies, the Garmin smartwatch algorithms may introduce misclassification of sleep stages, notably in distinguishing between light and deep sleep, which could influence the precision of specific stage-level metrics [ , , ].

Techniques: Derivative Assay

Journal: medRxiv

Article Title: Hidden in the Night: Wearable Sleep Assessment of Nocturnal Hypoglycaemia in Type 1 Diabetes

doi: 10.64898/2026.01.22.26344161

Figure Lengend Snippet: Structure of the dataset combining continuous glucose monitoring (CGM) metrics with smartwatch-derived sleep data, including physiological biomarkers, stage-level information, and summary sleep features.

Article Snippet: We conducted a comparative observational analysis of paired continuous glucose monitoring (CGM) and Garmin smartwatch data collected over 12 weeks from 17 adults with T1D.

Techniques: Derivative Assay