EMG-derived respiration signal using the fixed sample entropy during an Inspiratory load protocol

• Published in: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2015; pp. 1703 - 1706
• Main Authors: Estrada, Luis, Torres, Abel, Sarlabous, Leonardo, Jane, Raimon
• Format: Conference Proceeding Journal Article Publication
• Language: English
• Published: United States IEEE 01.08.2015; Institute of Electrical and Electronics Engineers (IEEE)
• Subjects: Adult; Band-pass filters; Biomedical engineering; Breathing activity; Diaphragm electromyographic signal; Diseases, Obstructive; Electrocardiography; Electrodes; Electromyography; EMG-derived respiration signal; Enginyeria biomèdica; Entropy; Fixed sample entropy; Healthy Volunteers; Humans; Inspiratory load protocol; Inspiratory mouth pressure; Insuficiència respiratòria; Lead-I configuration; Lungs; Malalties obstructives; Male; Mouth; Muscles; Protocols; Pulmons; Respiration waveform; Respiratory insufficiency; Respiratory muscle electrical activity; Respiratory Muscles - physiology; Respiratory Rate - physiology; Respiratory rate extraction; Àrees temàtiques de la UPC
• ISBN: 9781424492695; 1424492696
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/EMBC.2015.7318705

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 mouth 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.