Bower J S, Sandercock T G, Rothman E, Abbrecht P H, Dantzker D R
J Appl Physiol Respir Environ Exerc Physiol. 1984 Sep;57(3):913-6. doi: 10.1152/jappl.1984.57.3.913.
Diaphragmatic fatigue has been correlated with a change in the electromyogram recorded from the diaphragm (EMGdi), which suggests that the electromyogram is a potential clinical tool to detect respiratory muscle fatigue. Changes in the EMGdi have previously been quantified by using the power spectral parameters high-low ratio or mean frequency. In this study, we developed an autoregressive model of the EMG in an attempt to improve the analysis of the EMGdi. This model was tested on recordings of the EMGdi that were obtained from an esophageal electrode in five normal subjects breathing to fatigue through an inspiratory resistor. The data obtained from the autoregressive model were directly compared with data from the high-low ratio and mean frequency techniques. The autoregressive model showed an excellent correlation with mean frequency. Both techniques were superior to the high-low ratio measurement. Because the autoregressive model requires much less computation than mean frequency and can be easily implemented in real time on a minicomputer, we propose this as a preferable approach.
膈肌疲劳与从膈肌记录的肌电图（EMGdi）变化相关，这表明肌电图是检测呼吸肌疲劳的一种潜在临床工具。此前，EMGdi的变化已通过功率谱参数高低比或平均频率进行量化。在本研究中，我们开发了一种肌电图自回归模型，试图改进对EMGdi的分析。该模型在五名正常受试者通过吸气电阻器呼吸至疲劳时，从食管电极获得的EMGdi记录上进行了测试。将自回归模型获得的数据与高低比和平均频率技术的数据直接进行比较。自回归模型与平均频率显示出极好的相关性。这两种技术均优于高低比测量。由于自回归模型所需的计算量比平均频率少得多，并且可以很容易地在小型计算机上实时实现，因此我们建议将其作为一种更可取的方法。
