Voluntary Respiration Control: Signature Analysis by EEG

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 31; pp. 4624 - 4634
• Main Authors: Wang, Yue, Zhang, Yan, Zhang, Yaoxi, Wang, Zongyu, Guo, Weidong, Zhang, Yuru, Wang, Yuhui, Ge, Qinggang, Wang, Dangxiao
• Format: Journal Article
• Language: English
• Published: United States IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Brain - physiology; Consciousness; Correlation; EEG; Electrodes; Electroencephalography; Electroencephalography - methods; Entropy; Humans; Low frequencies; Monitoring; PLV; Respiration; Respiratory Rate; sample entropy; Scalp; Signature analysis; Task analysis; Training
• DOI: 10.1109/TNSRE.2023.3332458
• ISSN: 1534-4320; 1558-0210

The perception of voluntary respiratory consciousness is quite important in some situations, such as respiratory assistance and respiratory rehabilitation training, and the key signatures about voluntary respiration control may lie in the neural signals from brain manifested as electroencephalography (EEG). The present work aims to explore whether there exists correlation between voluntary respiration and scalp EEG. Evoke voluntary respiration of different intensities, while collecting EEG and respiration signal synchronously. Data from 11 participants were analyzed. Spectrum characteristics at low-frequency band were studied. Computation of EEG-respiration phase lock value (PLV) and EEG sample entropy were conducted as well. When breathing voluntarily, the 0-2 Hz band EEG power is significantly enhanced in frontal and right-parietal area. The distance between main peaks belonging to the two signals in 0-2 Hz spectrum graph tends to get smaller, while EEG-respiration PLV increases in frontal area. Besides, the sample entropy of EEG shows a trend of decreasing during voluntary respiration in both areas. There's a strong correlation between voluntary respiration and scalp EEG. Significance: The discoveries will provide guidelines for developing a voluntary respiratory consciousness identifying method and make it possible to monitor people's intention of respiration by noninvasive BCI.