Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise – A Pilot Regression-Based Study
Masaaki Hattori,1 Kazuya Yashiro2 1Department of Community Development, Tokai University, Sapporo, Hokkaido, Japan; 2Faculty of Information Technology, Kanagawa Institute of Technology, Atsugi, Kanagawa, JapanCorrespondence: Masaaki Hattori, Department of Community Development, Tokai University, 5-1...
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Dove Medical Press
2025-07-01
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| description | Masaaki Hattori,1 Kazuya Yashiro2 1Department of Community Development, Tokai University, Sapporo, Hokkaido, Japan; 2Faculty of Information Technology, Kanagawa Institute of Technology, Atsugi, Kanagawa, JapanCorrespondence: Masaaki Hattori, Department of Community Development, Tokai University, 5-1-1, Minamisawa, Minami-ku, Sapporo, 005-8601, Japan, Tel +81 11 571 1111 (ext 2423), Fax +81 11 571 7879, Email mhattori@tokai.ac.jpBackground: Blood lactate (BL) is a critical biomarker for assessing anaerobic metabolism and fatigue. Sweat lactate (SWL) and sweat rate (SWR) have been explored as non-invasive alternatives, but their capacity to estimate BL dynamics after short-term high-intensity exercise remains unclear.Purpose: This pilot study aimed to evaluate whether BL dynamics can be predicted using a regression model based on the time-series patterns of SWL and SWR measured by wearable sensors.Methods: Five healthy male athletes (three sprinters and two endurance runners) performed a 30-second Wingate anaerobic test. SWL and SWR were continuously monitored using a wearable electrochemical sensor and a ventilated capsule-type sweat rate meter. Capillary BL was sampled for 30 minutes post-exercise.Results: BL showed a delayed peak at 6.4 ± 1.2 min, while SWL and SWR exhibited biphasic responses. The second SWL peak (7.5 ± 2.2 min) aligned with the BL peak. Although peak-based correlations were not significant, Pearson correlations using time-series data revealed strong associations (r = 0.501– 0.933 for SWL; r = 0.515– 0.805 for SWR; all p < 0.001). A multivariate regression model using both variables predicted BL with high accuracy (R² = 0.763, RMSE = 1.612, MAE = 0.995, p < 0.001).Conclusion: These findings support the feasibility of a regression-based approach using sweat-derived time-series data to non-invasively estimate BL dynamics after high-intensity exercise.Keywords: sweat lactate, sweat rate, blood lactate, wearable sensor, high-intensity exercise, non-invasive |
| format | Article |
| id | doaj-art-16f1c226f2134268af0b4fdf2411f0bc |
| institution | Kabale University |
| issn | 1179-1543 |
| language | English |
| publishDate | 2025-07-01 |
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| series | Open Access Journal of Sports Medicine |
| spelling | doaj-art-16f1c226f2134268af0b4fdf2411f0bc2025-08-20T03:31:59ZengDove Medical PressOpen Access Journal of Sports Medicine1179-15432025-07-01Volume 16Issue 199105105297Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise &ndash; A Pilot Regression-Based StudyHattori M0Yashiro K1Community DevelopmentInformation and Technology Sports ScienceMasaaki Hattori,1 Kazuya Yashiro2 1Department of Community Development, Tokai University, Sapporo, Hokkaido, Japan; 2Faculty of Information Technology, Kanagawa Institute of Technology, Atsugi, Kanagawa, JapanCorrespondence: Masaaki Hattori, Department of Community Development, Tokai University, 5-1-1, Minamisawa, Minami-ku, Sapporo, 005-8601, Japan, Tel +81 11 571 1111 (ext 2423), Fax +81 11 571 7879, Email mhattori@tokai.ac.jpBackground: Blood lactate (BL) is a critical biomarker for assessing anaerobic metabolism and fatigue. Sweat lactate (SWL) and sweat rate (SWR) have been explored as non-invasive alternatives, but their capacity to estimate BL dynamics after short-term high-intensity exercise remains unclear.Purpose: This pilot study aimed to evaluate whether BL dynamics can be predicted using a regression model based on the time-series patterns of SWL and SWR measured by wearable sensors.Methods: Five healthy male athletes (three sprinters and two endurance runners) performed a 30-second Wingate anaerobic test. SWL and SWR were continuously monitored using a wearable electrochemical sensor and a ventilated capsule-type sweat rate meter. Capillary BL was sampled for 30 minutes post-exercise.Results: BL showed a delayed peak at 6.4 ± 1.2 min, while SWL and SWR exhibited biphasic responses. The second SWL peak (7.5 ± 2.2 min) aligned with the BL peak. Although peak-based correlations were not significant, Pearson correlations using time-series data revealed strong associations (r = 0.501– 0.933 for SWL; r = 0.515– 0.805 for SWR; all p < 0.001). A multivariate regression model using both variables predicted BL with high accuracy (R² = 0.763, RMSE = 1.612, MAE = 0.995, p < 0.001).Conclusion: These findings support the feasibility of a regression-based approach using sweat-derived time-series data to non-invasively estimate BL dynamics after high-intensity exercise.Keywords: sweat lactate, sweat rate, blood lactate, wearable sensor, high-intensity exercise, non-invasivehttps://www.dovepress.com/short-report-estimating-blood-lactate-dynamics-from-sweat-lactate-and--peer-reviewed-fulltext-article-OAJSM: sweat lactatesweat rateblood lactatewearable sensorhigh-intensity exercisenon-invasive |
| spellingShingle | Hattori M Yashiro K Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise &ndash; A Pilot Regression-Based Study Open Access Journal of Sports Medicine : sweat lactate sweat rate blood lactate wearable sensor high-intensity exercise non-invasive |
| title | Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise &ndash; A Pilot Regression-Based Study |
| title_full | Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise &ndash; A Pilot Regression-Based Study |
| title_fullStr | Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise &ndash; A Pilot Regression-Based Study |
| title_full_unstemmed | Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise &ndash; A Pilot Regression-Based Study |
| title_short | Short Report: Estimating Blood Lactate Dynamics from Sweat Lactate and Sweat Rate After High-Intensity Exercise &ndash; A Pilot Regression-Based Study |
| title_sort | short report estimating blood lactate dynamics from sweat lactate and sweat rate after high intensity exercise amp ndash a pilot regression based study |
| topic | : sweat lactate sweat rate blood lactate wearable sensor high-intensity exercise non-invasive |
| url | https://www.dovepress.com/short-report-estimating-blood-lactate-dynamics-from-sweat-lactate-and--peer-reviewed-fulltext-article-OAJSM |
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