ArticleScientific reports2023
Estimation of maximal lactate steady state using the sweat lactate sensor.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- The global scientific evolution of cardiopulmonary performance and threshold research in sports sciences during 2010-2025: a comparative bibliometric analysis based on web of science and scopus.Frontiers in research metrics and analytics · 2026Pooled it
- Sweat lactate sensor for detecting anaerobic threshold in heart failure: a prospective clinical trial (LacS-001).Scientific reports · 2024Trial
- Validation of aerobic threshold assessment using a sweat lactate sensor during arm crank exercise by healthy adults.Physiological reports · 2026Article
- Minimally invasive prediction of blood lactate during incremental exercise via heart rate, core body temperature, and sweat-derived indices.Scientific reports · 2026Article
- Feasibility study of a novel wearable sweat sensor for anaerobic threshold determination.Scientific reports · 2025Article
- A Granular Hydrogel-Enabled Wearable Electrochemical Biosensing Platform for Continuous Non-Invasive Sweat Lactate Detection.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Anaerobic threshold using sweat lactate sensor under hypoxia.Scientific reports · 2023Article
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Authors and funding
15 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A simple, non-invasive algorithm for maximal lactate steady state (MLSS) assessment has not been developed. We examined whether MLSS can be estimated from the sweat lactate threshold (sLT) using a novel sweat lactate sensor for healthy adults, with consideration of their exercise habits. Fifteen adults representing diverse fitness levels were recruited. Participants with/without exercise habits were defined as trained/untrained, respectively. Constant-load testing for 30 min at 110%, 115%, 120%, and 125% of sLT intensity was performed to determine MLSS. The tissue oxygenation index (TOI) of the thigh was also monitored. MLSS was not fully estimated from sLT, with 110%, 115%, 120%, and 125% of sLT in one, four, three, and seven participants, respectively. The MLSS based on sLT was higher in the trained group as compared to the untrained group. A total of 80% of trained participants had an MLSS of 120% or higher, while 75% of untrained participants had an MLSS of 115% or lower based on sLT. Furthermore, compared to untrained participants, trained participants continued constant-load exercise even if their TOI decreased below the resting baseline (P < 0.01). MLSS was successfully estimated using sLT, with 120% or more in trained participants and 115% or less in untrained participants. This suggests that trained individuals can continue exercising despite decreases in oxygen saturation in lower extremity skeletal muscles.
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