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文章运用多尺度熵的方法，对低氧环境下血氧序列进行分析。研究发现，与传统的均值分析法相比，多尺度熵分析能反映机体适应低氧的动态过程；而与只在最小尺度上估计序列长度m与m＋1之间不同的样本熵相比，多尺度熵计算时间序列在多个尺度上的样本熵值，体现了时间序列在尺度上的无规则度，可以更全面的提取血氧信号的有效信息。研究结果表明，多尺度熵的血氧序列分析能对人的低氧耐力进行辨识，是一种研究机体低氧调节过程的可靠分析方法。研究还发现，多次的低氧刺激会对人体产生习服作用，机体表现出对低氧环境的记忆性。“,”Multi-scale entropy was introduced to analyze the blood oxygen sequence under hypoxic environment. Compared with mean analytical method, blood oxygen sequence analysis based on multi-scale entropy can reflect the dynamic adjustment mechanism of body hypoxia better. Multi-scale entropy, which is different from sample entropy that just estimates the difference between sequence lengthm andm+1 on the smallest scale and ignores other scales, calculates sample entropy of time series on multiple scales and relfects the irregular degree of time series on scales. The result shows that blood oxygen sequence analysis based on multi-scale entropy can identify human hypoxia endurance. This method is a reliable analytical method for studying the mechanism of hypoxic regulation of human body. The result also shows that repeated hypoxic stimulation will produce acclimatization effects on the human body which shows memory of hypoxia environment.