Suppr超能文献

膈肌肌电图功率谱矩的多变量分析。

Multivariate analysis of diaphragm EMG power spectral moments.

作者信息

Adams J M, Aldrich T K, Arora N S, Rochester D F

出版信息

Comput Biomed Res. 1984 Apr;17(2):163-74. doi: 10.1016/0010-4809(84)90029-6.

Abstract

A single derived index of the power spectrum of the diaphragm electromyogram (EMG) has been used in detecting fatigue. Additional information in the EMG could be used to study diaphragm function in other respiratory conditions. Diaphragm EMGs and calculated power spectra at 12 frequencies were measured in normal subjects and patients with severe chronic obstructive pulmonary disease during several respiratory maneuvers both before and after treadmill exercise to dyspnea. The power spectra were characterized by the first five moments. Changes in the EMG were similar when assessed by multivariate analysis of variance of the spectral estimates or of the moments. Factor analysis provided two latent variables that correlated with the first and second moment respectively. The first moment was found to be the most sensitive single discriminant of fatigue and is only slightly improved by adding other information. It is concluded that the first and second moments of the EMG power spectra provide a concise, parsimonious description of the changes in the EMG.

摘要

膈肌肌电图(EMG)功率谱的单一衍生指标已被用于检测疲劳。EMG中的其他信息可用于研究其他呼吸状况下的膈肌功能。在正常受试者和重度慢性阻塞性肺疾病患者进行跑步机运动至呼吸困难前后的几次呼吸动作过程中,测量了膈肌肌电图以及12个频率下计算出的功率谱。功率谱通过前五个矩进行表征。通过对频谱估计值或矩进行多变量方差分析评估时,肌电图的变化相似。因子分析提供了两个分别与第一矩和第二矩相关的潜在变量。发现第一矩是疲劳最敏感的单一判别指标,添加其他信息后仅略有改善。得出的结论是,肌电图功率谱的第一矩和第二矩对肌电图的变化提供了简洁、简约的描述。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验