Can Wearable Sweat Lactate Sensors Contribute to Sports Physiology?

Abstract

The rise of wearable sensors to measure lactate content in human sweat during sports activities has attracted the attention of physiologists given the potential of these “analytical tools” to provide real-time information. Beyond the assessment of the sensing technology per se , which, in fact, has not rigorously been validated yet in controlled conditions, there are many open questions about the true usefulness of such wearable sensors in real scenarios. On the one hand, the evidence for the origin of sweat lactate (e.g., via the sweat gland, derivation from blood, or other alternative mechanisms), its high concentration (1–25 mM or even higher) compared to levels in the blood, and the possible correlation between different biofluids (particularly blood) is rather contradictory and generates vivid debate in the field. On the other hand, it is important to point out that accurate detection of sweat lactate is highly dependent on the procedure used to collect and/or reach the fluid, and this can likely explain the large discrepancies reported in the literature. In brief, this paper provides our vision of the current state of the field and a thoughtful evaluation of the possible reasons for present controversies, together with an analysis of the impact of wearable sweat lactate sensors in the physiological context. Finally, although there is not yet overwhelming scientific evidence to provide an unequivocal answer to whether wearable sweat lactate sensors can contribute to sports physiology, we still understand the importance to bring this challenging question up-front to create awareness and guidance in the development, validation, and implementation of wearable sensors.

Realtime Monitoring of Local Sweat Rate Kinetics during Constant-Load Exercise Using Perspiration-Meter with Airflow Compensation System

“…It is possible that these present findings with LSR kinetics will contribute to interpreting the result obtained via real-monitoring biomarkers in sweat, which is beneficial for the evaluation of body status during exercise. The reason for this is that several analytes have the possibility to provide helpful information about body status by detecting the flexion point in a continually obtained value during exercise [ 9 , 10 , 11 , 33 ]. Further research or application in sports settings to the monitoring of analytes in sweat during constant-load exercise needs to interpret obtained results on the premise of the existence of two flexion points in LSR kinetics.…”

Scientific athletics training: flexible sensors and wearable devices forkineses monitoring applications

“…汗液乳酸的测定可以为血液乳酸测定提供了一种无创的检测方法(见图 6 a) [101] ,但是目前报道中汗液乳 酸与血液乳酸关相关性较小 [102] . 为了进一步拓宽汗液中乳酸检测的实际应用, 研究人员尝试进一步探讨 汗液中测量的乳酸水平与血液中乳酸水平的关系.…”

“…图 6 基于电化学生物传感器对乳酸分子监测的应用. (a) 基于可穿戴传感器用于运动实时乳酸监测 [101] ; (b) 一种侵入式血乳 酸监测传感器的结构 [99] ; (c) 基于非侵入式的电化学生物乳酸传感器, 用于实时连续监测汗液乳酸动态变化 [102] ; (d) 基于多功 能的比色汗液分析微流控装置，实现汗液中多成分的监测 [106] . Figure 6.…”

“…Wearable lactate biosensor in sweat for real-time movement monitoring. Reproduced with permission [101] Copyright 2021, American Chemical Society; (b) Schematic structure of the invasive blood lactate sensor; Reproduced with permission [99] Copyright 2021, American Chemical Society; (c) A non-invasive electrochemical lactate sensor to monitor of sweat lactate. Reproduced with permission [102] Copyright 2013, American Chemical Society; (d) Colorimetric sweat analysis microfluidic device to monitor of multiple components in sweat.…”

Monitoring and Visualization of Physical Exercise Physiological Indicators Driven by Discrete Data

“…e keywords of statistical scientific research literature or the correlation relationship of other cited literature, or the cooperative relationship between the authors of statistical papers, the cooccurrence of complex network form of network visualization can visually represent the intersection of disciplines, which greatly improves the efficiency of bibliometric analysis [22][23][24][25]. Scholars in the field of complex networks mainly focus on the dynamics of network propagation, the convergence and stability of neural networks, and other related research and make corresponding econometric models and algorithms.…”