与分级运动测试相比，智能手表得出的乳酸阈心率和配速估计值的有效性。

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

作者信息

Lu Changda, Cui Wei, Zhu Zheng, Wu Yiwei, Xing Qingjun, Pan Bingyu, Shen Yanfei

机构信息

School of Sport Science, Beijing Sport University, Beijing, China.

School of Sports Engineering, Beijing Sport University, Beijing, China.

出版信息

Front Physiol. 2025 Jul 4;16:1621996. doi: 10.3389/fphys.2025.1621996. eCollection 2025.

DOI:10.3389/fphys.2025.1621996

PMID:40740423

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12309276/

Abstract

BACKGROUND

Quantifying exercise intensity through the lactate threshold (LT) is crucial for optimizing athletic training regimes. Traditional methods like maximal lactate steady state and graded exercise testing are valid but invasive and costly. Advances in smartwatch technology offer a non-invasive alternative for monitoring LT, though their measurement protocols and outcomes have been less validated.

METHODS

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. One hundred healthy recreational runners underwent indoor graded exercise tests followed by outdoor tests using Huawei (n = 100), Garmin (n = 23), and Coros (n = 17) smartwatches to compare differences in testing protocols and LT HR and LT Pace.

RESULTS

The success rates for a single test were 78% for Huawei®, 65.22% for Garmin®, and 47.06% for Coros®. For LT HR, no significant differences were observed between smartwatch and DmaxMod estimates across all devices (p > 0.05). The Huawei® watch showed MAE = 10.66 bpm, MAPE = 6.32%; Garmin®: MAE = 11.44 bpm, MAPE = 7.15%; Coros®: MAE = 8.93 bpm, MAPE = 5.95%. Corresponding Pearson correlation coefficients ranged from r = 0.13 to 0.67, and values ranged from 0.02 to 0.45. In contrast, LT Pace predictions demonstrated significant overestimation for all devices. Huawei® reported the smallest error (MAE = 1.22 km/h, MAPE = 12.70%, p = 0.01, r = 0.88, = 0.78), followed by Garmin® (MAE = 2.17 km/h, MAPE = 25.78%, p < 0.01, r = 0.73, = 0.53), and Coros® (MAE = 1.93 km/h, MAPE = 22.63%, p = 0.08, r = 0.79, = 0.62). Bland-Altman plots confirmed systematic biases and variable agreement patterns, particularly for LT Pace.

CONCLUSION

Smartwatches are capable of providing estimates of LT HR and LT Pace in recreational runners, although they tend to overestimate LT Pace and overall accuracy remains to be improved.

摘要

背景

通过乳酸阈值（LT）量化运动强度对于优化运动训练方案至关重要。传统方法如最大乳酸稳态和分级运动测试有效，但具有侵入性且成本高昂。智能手表技术的进步为监测LT提供了一种非侵入性替代方法，尽管其测量方案和结果的验证较少。

方法

本研究评估了三款主流智能手表（华为GT Runner®、佳明Forerunner 265®或265s®以及高驰Pace3®）在估计乳酸阈值心率（LT HR）和配速（LT Pace）方面的有效性，并将其与实验室标准下改良Dmax方法的测量方案和结果进行比较。100名健康的休闲跑步者进行了室内分级运动测试，随后使用华为（n = 100）、佳明（n = 23）和高驰（n = 17）智能手表进行户外测试，以比较测试方案以及LT HR和LT Pace的差异。

结果

单次测试的成功率华为®为78%，佳明®为65.22%，高驰®为47.06%。对于LT HR，所有设备的智能手表估计值与DmaxMod估计值之间均未观察到显著差异（p > 0.05）。华为®手表的平均绝对误差（MAE）= 10.66次/分钟，平均绝对百分比误差（MAPE）= 6.32%；佳明®：MAE = 11.44次/分钟，MAPE = 7.15%；高驰®：MAE = 8.93次/分钟，MAPE = 5.95%。相应的皮尔逊相关系数范围为r =从0.13至0.67，值范围为0.02至0.45。相比之下，LT Pace预测显示所有设备均存在显著高估。华为®报告的误差最小（MAE = 1.22千米/小时，MAPE = 12.70%，p = 0.01，r = 0.88， = 0.78），其次为佳明®（MAE = 2.17千米/小时，MAPE = 25.78%，p < 0.01，r = 0.73， = 0.53），高驰®（MAE = 1.93千米/小时，MAPE = 22.63%，p = 0.08，r = 0.79， = 0.62）。布兰德 - 奥特曼图证实了系统偏差和可变的一致性模式，特别是对于LT Pace。