Romarate Ander, Pinedo-Jauregi Aitor, Feldmann Andri, Viribay Aitor, Santos-Concejero Jordan
Emen4sport, Leioa, Spain.
Department of Physical Education and Sport, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain.
Eur J Sport Sci. 2025 Aug;25(8):e70025. doi: 10.1002/ejsc.70025.
The accurate detection of several physiological milestones, such as maximal fat oxidation (MFO), is an important factor for cycling performance and for programming effective and individualised training. However, the procedure to identify the MFO is often too complex and expensive. Near-infrared spectroscopy (NIRS) technology provides a noninvasive measurement that can be used to detect different physiological variables. The aim of this study was to assess the validity of utilising the muscular oxygen saturation visualisation methodology for the identification of the MFO point in trained cyclists. Twenty-two recreational endurance-trained cyclists (19 men and 3 women; age: 27.9 ± 5.4 years; body mass: 69.7 ± 7.1 kg and VO: 60.3 ± 7.0 mL/kg/min) performed a submaximal and maximal exhaustion test. All the data were collected on a single day. The validity of the visualisation methodology for the maximal fat oxidation point was analysed against a gas analyser. The detection of maximal fat oxidation (MFO) using the methodology and device employed does not appear to accurately specify the precise point at which MFO occurs (bias = 90 ± 218 s and LOA = 429 s). However, our results indicate that it may be a valid technique for identifying the MFO zone; biases were HR = 4.7 ± 11.9 bpm, VO = 1.49 ± 5.7 mL/kg/min and power = 19.5 ± 31.2 W, whereas the concordance coefficients were 0.783, 0.243 and 0.170, respectively. It is not possible to detect MFO using NIRS device. However, it is possible to detect a general zone in which MFO occurs.
准确检测多个生理指标，如最大脂肪氧化（MFO），是影响骑行表现以及制定有效且个性化训练计划的重要因素。然而，识别MFO的过程通常过于复杂且成本高昂。近红外光谱（NIRS）技术提供了一种可用于检测不同生理变量的非侵入性测量方法。本研究的目的是评估利用肌肉氧饱和度可视化方法来识别训练有素的自行车运动员MFO点的有效性。22名接受过耐力训练的业余自行车运动员（19名男性和3名女性；年龄：27.9±5.4岁；体重：69.7±7.1千克；最大摄氧量：60.3±7.0毫升/千克/分钟）进行了次最大强度和最大力竭测试。所有数据均在同一天收集。针对气体分析仪分析了最大脂肪氧化点可视化方法的有效性。使用所采用的方法和设备检测最大脂肪氧化（MFO）似乎无法准确确定MFO发生的精确时间点（偏差=90±218秒，一致性界限=429秒）。然而，我们的结果表明，它可能是一种识别MFO区域的有效技术；偏差分别为心率=4.7±11.9次/分钟、最大摄氧量=1.49±5.7毫升/千克/分钟和功率=19.5±31.2瓦，而一致性系数分别为0.783、0.243和0.170。使用NIRS设备无法检测到MFO。然而，可以检测到MFO发生的大致区域。
