AI Insight
Researchers developed a non-invasive method to continuously monitor lactate levels in living subjects using near-infrared spectroscopy in the 1600-1850 nm wavelength range. The middle phalanx of the finger was identified as the optimal measurement site, achieving high prediction accuracy within single days, though performance degraded across different days due to spectral drift and physiological changes. A dynamic offset-correction procedure was successfully implemented to maintain stable prediction accuracy across extended time periods and different individuals.
Why it matters
This technology could enable real-time, painless lactate monitoring for athletes optimizing training intensity and for medical settings where lactate is a critical indicator of tissue oxygen deprivation or metabolic stress. The non-invasive nature eliminates the need for repeated blood draws, potentially improving patient comfort and enabling continuous monitoring in clinical and sports applications.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
We present a non-invasive approach for continuous monitoring of lactate dynamics in-vivo using near-infrared (NIR) spectroscopy. Lactate-related spectral features were measured non-invasively within the overtone region (1600 -1850 nm). Several anatomical measurement sites were evaluated, and the middle phalanx of the dorsal finger emerged as the most promising location due to its superior spectral quality and stable tissue perfusion, becoming the exclusive site for all further experiments. Across multiple exercise sessions, predictive models achieved high within-day accuracy (R^2 [≥] 0.8), while cross-day performance was affected by spectral drift and physiological variability. A dynamic offset-correction procedure effectively mitigated these baseline shifts, enabling stable prediction accuracy across days, weeks, and subjects. These findings demonstrate the feasibility of NIR-based lactate estimation and highlight the importance of adaptive correction strategies for reliable long-term, non-invasive monitoring.
Source: Non-invasive in vivo lactate monitoring via NIR spectroscopy