Characterizing Signal Quality of Three Common Respiratory Sensing Modalities in the Context of Stress and Peripheral Nerve Stimulation

Stress leads to widespread peripheral effects, including manifestations of respiratory distress. The combination of respiratory monitoring and non-invasive Peripheral Nerve Stimulation (PNS) represents a promising technological approach to quantify and reduce the physiological manifestations of stress. Such technologies require non-invasive, reliable respiratory information with adequate signal quality during various conditions. In this work, we computed an established respiratory quality index (RQI) on four respiratory signals derived from three common respiratory sensing modalities (respiratory effort (RSP), electrocardiogram-derived respiration (EDR), and Impedance Pneumography (IP)) in a complex stress protocol wherein 15 subjects underwent three stressors while receiving 1 of 3 active PNS modalities or sham. Our results indicate that the RQI of all signals changed substantially throughout the protocol with a maximal reduction from baseline of 21.28% (p < 0.001) during stressors involving speech. Further, RSP and IP resulted in the highest average quality and both were significantly higher in quality than the two EDR signals (p < 0.001). These results provide unique information that may inform the design of new technologies and studies leveraging respiratory markers for continuous stress detection and mitigation.