Scientific Reports (Jun 2023)

Estimation of maximal lactate steady state using the sweat lactate sensor

  • Yuki Muramoto,
  • Daisuke Nakashima,
  • Tsubasa Amano,
  • Tomota Harita,
  • Kazuhisa Sugai,
  • Kyohei Daigo,
  • Yuji Iwasawa,
  • Genki Ichihara,
  • Hiroki Okawara,
  • Tomonori Sawada,
  • Akira Kinoda,
  • Yuichi Yamada,
  • Takeshi Kimura,
  • Kazuki Sato,
  • Yoshinori Katsumata

DOI
https://doi.org/10.1038/s41598-023-36983-8
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 10

Abstract

Read online

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.