您好,欢迎访问中国农业科学院 机构知识库!

EMG-Derived Respiration Signal using the Fixed Sample Entropy during an Inspiratory Load Protocol

文献类型: 会议论文

第一作者: Luis Estrada

作者: Luis Estrada 1 ; Abel Torres 2 ; Leonardo Sarlabous 3 ; Raimon Jané 1 ;

作者机构: 1.the Universitat Politécnica de Catalunya (UPC), the Institut de Bioenginyeria de Catalunya (IBEC) and the Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), c/. Baldiri Reixac 4, 08028, Barcelona, Spain.

2.the Escola Universitària d'Enginyeria Tècnica Industrial de Barcelona (EUETIB), Barcelona, Spain.

3.the CIBER-BBN and the IBEC

关键词: fSampEn;EMGdi;EMGDR

会议名称: Annual International Conference of the IEEE Engineering in Medicine and Biology Society

主办单位:

页码: 1703-1706

摘要: Extracting clinical information from one single measurement represents a step forward in the assessment of the respiratory muscle function. This attracting idea entails the reduction of the instrumentation and fosters to develop new medical integrated technologies. We present the use of the fixed sample entropy (fSampEn) as a more direct method to non-invasively derive the breathing activity from the diaphragm electromyographic (EMGdi) signal, and thus to extract the respiratory rate, an important vital sign which is cumbersome and time-consuming to be measured by clinicians. fSampEn is a method to evaluate the EMGdi activity that is less sensitive to the cardiac activity (ECG) and its application has proven to be useful to evaluate the load of the respiratory muscles. The behavior of the proposed method was tested in signals from two subjects that performed an inspiratory load protocol, which consists of increments in the inspiratory mouth pressure (P_(mouth)). Two respiratory signals were derived and compared to the P_(mou)th signal: the ECG-derived respiration (EDR) signal from the lead-I configuration, and the EMG-derived respiration (EMGDR) signal by applying the fSampEn method over the EMGdi signal. The similitude and the lag between signals were calculated through the cross-correlation between each derived respiratory signal and the P_(mouth). The EMGDR signal showed higher correlation and lower lag values (≥ 0.91 and ≤ 0.70 s, respectively) than the EDR signal (≥ 0.83 and ≤0.99 s, respectively). Additionally, the respiratory rate was estimated with the P_(mouth), EDR and EMGDR signals showing very similar values. The results from this preliminary work suggest that the fSampEn method can be used to derive the respiration waveform from the respiratory muscle electrical activity.

分类号: Q81-53

  • 相关文献
作者其他论文 更多>>