联合近红外光谱术的多生理参数监测及运动能力评估

发布时间：2018-04-11 13:38

  本文选题：有氧运动能力 + 近红外光谱术　； 参考：《华中科技大学》2012年博士论文

【摘要】：进行有氧运动能力（AEC）评估，可获得最大摄氧量（.V O_(2max)）、乳酸阈（LT）、通气阈（GET）、心率阈（HRT）等全身性AEC指标。它们对运动员选材、训练等有重要指导意义。然而，这些指标通常是利用全身性生理监测技术（如心肺功能监测、血液分析技术等）获得的，测量时需要配戴面罩或者采血，会使被试感觉不适或为有损测量。另外，仅利用全身性监测技术仍不能解释某些运动生理现象，例如：拥有相似AEC指标的群体，其运动成绩却有显著差别；高运动水平人群的机能效率反而低下。近红外光谱术（NIRS）和表面肌电技术（sEMG）可以分别无损、实时地监测局部肌肉氧代谢过程和神经电活动。考虑到复杂运动有多块肌肉参与，且肌肉间贡献可能不一样。本文联合局部和全身生理监测，在不同的被试类型、运动模式中，监测和分析多块局部肌肉和全身性运动生理参数变化，更全面地对AEC进行评估。 本文联合NIRS、sEMG和全身性生理监测技术，测量8名划船运动员、31名蹼泳运动员及20名散打运动员在递增运动测试（IET）中的局部肌肉和全身性生理参数响应情况，并分析肱二头肌（BB）、股外侧肌（VL）、腓肠肌外侧头（GL）、股直肌（RF）、股内侧肌（VM）中的一块或多块肌肉的氧代谢能力及其与全身性AEC指标之间的联系。 划船运动员在划船IET中的BB和VL处反映肌肉氧代谢能力的肌氧拐点（Bp）（BpBB：45(3.8)%.V O_(2max)，BpVL：55.6(2.4)%.V O_(2max)）均与全身性AEC指标显著相关（r0.81, p 0.05）。在高水平运动员中，BpBB和BpVL出现更晚，而且两者的出现时间更接近。即高水平运动员局部肌肉的氧利用能力更高，而且肌群间不同肌肉氧利用能力的匹配程度更高，这从局部肌氧的角度给出了高水平运动员能够取得更好运动成绩的生理原因。 蹼泳运动员在自行车IET中的BpVL（57.7(1.4)%.V O_(2max)）和GL处的Bp（BpGL，65.7(1.7)%.V O_(2max)）均与全身性AEC指标显著相关（r0.839, p 0.01）。但是BpVL早于BpGL出现，这可能是由于VL在自行车IET中贡献更多，但氧化性肌纤维比例比GL低而导致的。分别利用BpVL和BpGL跟AEC指标进行线性拟合，发现BpVL的拟合优度高于BpGL的拟合优度（p 0.05），表明BpVL预测AEC指标的能力更好，说明利用NIRS获取Bp并进行AEC评估时，需要注意肌肉差异。高水平运动员在IET中机能效率低，即摄氧量随功率增加而增加的速率更快于低水平运动员（p0.05）。与之对应的是，高水平运动员的肌氧下降速率更慢（p 0.05），这从局部肌氧的角度给出了高水平运动员的机能效率反而低的生理原因。 散打运动员在递增静力性伸膝IET中，VL、RF和VM处的Bp分别在45.0(1.7)、46.6(2.1)和45.3(2.2)最大自主收缩力量百分比（%MVC）处出现，VL、RF和VM处的sEMG阈（EMGT）分别在45.3(1.9)、49.5(2.2)和49.2(1.9)%MVC处出现，三块肌肉处的Bp、EMGT均与HRT之间没有显著差异（p0.05），表明在涉及肌肉少的静力性伸膝IET中，局部肌肉的生理阈值（Bp、EMGT）与全身性生理阈值之间没有显著差异，这可能是由于此时全身性生理响应主要是由少量肌肉收缩所致。当比较肌群内不同肌肉Bp和EMGT的差异时，，没有发现肌群内肌肉间的显著差异（p0.05）。这表明肌群内不同肌肉间的氧利用能力差异与肌群间不同肌肉之间的氧利用能力差异，可能存在不一样的规律，但这需要进一步研究。 综上所述，联合NIRS、sEMG及全身性生理监测技术，能够从局部到全身的角度进行更全面的AEC评估。
[Abstract]:Aerobic exercise capacity (AEC) assessment, can obtain the maximal oxygen uptake (.V O_ (2max)), lactate threshold (LT), ventilatory threshold (GET), heart rate threshold (HRT) and systemic AEC index. On the selection of athletes, training has an important guiding significance. However, these indicators are usually is the use of systemic physiological monitoring techniques (such as heart and lung function monitoring, blood analysis technology) obtained, when measuring the need to wear a mask or blood, will make the subjects feel discomfort or loss measurement. In addition, using only systemic monitoring technology still can not explain some physiological phenomenon, for example, have a similar AEC the index group, its performance has a significant difference; the crowd high sports level function but the efficiency is low. Near infrared spectroscopy (NIRS) and surface electromyography (sEMG) technology can be respectively nondestructive, real-time monitoring of local muscle oxygen metabolism and neuronal activity. Considering the complexity of motion There are many muscles involved, and the contribution between muscles may be different. In this paper, local and whole body physiological monitoring is applied to monitor and analyze the changes of multiple local muscle and systemic exercise physiological parameters in different types of subjects and exercise modes, so as to evaluate AEC more comprehensively.
In this paper, combined with NIRS, sEMG and systemic physiological monitoring technology, measuring 8 rowing athletes, 31 athletes and 20 athletes of Sanda Athletes in incremental exercise test (IET) local muscle and systemic physiological parameters in response, and analysis of the biceps brachii (BB), vastus lateralis (VL), the lateral head of the gastrocnemius muscle (GL) (RF), rectus femoris, vastus medialis (VM) between the oxygen metabolism ability of one or more blocks in muscle and systemic AEC index.
At BB and VL in rowing athletes rowing in IET reflect the muscle oxygen metabolism ability of muscle oxygen inflection point (Bp) (BpBB:45 (3.8)%.V O_ (2max), BpVL:55.6 (2.4)%.V O_ (2max)) were significantly associated with systemic AEC index (r0.81, P 0.05). In high level athletes BpBB, and BpVL appeared later, and both appear closer to the time. The high level athletes of local muscle oxygen utilization ability is higher, and the muscles between different muscle oxygen utilization ability, higher degree, the physiological causes of muscle oxygen from the local point of view gives a high level athletes to achieve better performance.
In the fin swimming athletes bike IET BpVL (57.7 (1.4)%.V O_ (2max) and GL (Bp) BpGL, 65.7 (1.7)%.V O_ (2max)) were significantly associated with systemic AEC index (r0.839, P 0.01). But BpVL earlier than BpGL, which may be due to VL in the bicycle IET to contribute more, but oxidative muscle fiber ratio is lower than that of GL caused by BpVL and BpGL respectively. The AEC index with linear fitting, BpVL found that the goodness of fit is higher than that of BpGL (P 0.05), BpVL showed better ability to predict the AEC index, that is obtained by using the NIRS and Bp AEC evaluation, need to pay attention to the difference of muscle. High level athletes in IET during low efficiency, namely oxygen uptake with the power increases faster than the low level athletes (P0.05). The corresponding is, muscle oxygen high level athletes decreased slower (P 0.05), from the local muscle the angle of the high level of oxygen The physiological reason that the athlete's functional efficiency is low.
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