Surface mechanomyography and electromyography provide non-invasive indices of inspiratory muscle force and activation in healthy subjects

Abstract

The current gold standard assessment of human inspiratory muscle function involves using invasive measures of transdiaphragmatic pressure (P_di) or crural diaphragm electromyography (oesEMG_di). Mechanomyography is a non-invasive measure of muscle vibration associated with muscle contraction. Surface electromyogram and mechanomyogram, recorded transcutaneously using sensors placed over the lower intercostal spaces (sEMG_lic and sMMG_lic respectively), have been proposed to provide non-invasive indices of inspiratory muscle activation, but have not been directly compared to gold standard P_di and oesEMG_di measures during voluntary respiratory manoeuvres. To validate the non-invasive techniques, the relationships between P_di and sMMG_lic, and between oesEMG_di and sEMG_lic were measured simultaneously in 12 healthy subjects during an incremental inspiratory threshold loading protocol. Myographic signals were analysed using fixed sample entropy (fSampEn), which is less influenced by cardiac artefacts than conventional root mean square. Strong correlations were observed between: mean P_di and mean fSampEn |sMMG_lic| (left, 0.76; right, 0.81), the time-integrals of the P_di and fSampEn |sMMG_lic| (left, 0.78; right, 0.83), and mean fSampEn oesEMG_di and mean fSampEn sEMG_lic (left, 0.84; right, 0.83). These findings suggest that sMMG_lic and sEMG_lic could provide useful non-invasive alternatives to P_di and oesEMG_di for the assessment of inspiratory muscle function in health and disease.

Figure 1

Measurements recorded during the inspiratory threshold loading protocol in a healthy subject. Two respiratory cycles are shown for quiet resting breathing and inspiratory threshold loads equivalent to 12%, 24%, 36%, 48%, and 60% of PImax (left to right). The oesEMG_di signal corresponds to the electrode pair 1.

Figure 2

RMS and fSampEn time-series of EMG and MMG signals shown in Fig. 1. Two respiratory cycles are shown for quiet breathing and 12%, 24%, 36%, 48%, and 60% of PImax (left to right).

Figure 3

Relationship between RMS- and fSampEn-derived measures of oesEMGdi. Data points represent median and interquartile range of the 120 respiratory cycles of the twelve study subjects for each load. The group mean correlation coefficient, ρ, of the twelve subjects was calculated using the Fisher z-transform. Dashed lines show the order of execution of the inspiratory threshold loads.

Figure 4

Measures of inspiratory muscle force and activation during inspiratory threshold loading. Data points represent median and interquartile range of the 120 respiratory cycles of the twelve study subjects for each load. Dashed lines show the order of execution of the inspiratory threshold loads.

Figure 5

Relationship between invasive and non-invasive measures of inspiratory muscle force output recorded from the left and right sides, calculated as the mean (a,b) and time-integral (c,d) of the P_di and fSampEn |sMMG_lic| signals. Data points represent median and interquartile range of the 120 respiratory cycles of the twelve study subjects for each load. The group mean correlation coefficients, ρ, of the twelve subjects were calculated using the Fisher z-transform. Dashed lines show the order of execution of the inspiratory threshold loads.

Figure 6

Relationship between invasive and non-invasive measures of inspiratory muscle electrical activation recorded from the left (a) and right (b) sides, calculated as the mean of the fSampEn oesEMG_di and sEMG_lic signals. Data points represent median and interquartile range of the 120 respiratory cycles of the twelve study subjects for each load. The group mean correlation coefficients, ρ, of the twelve subjects were calculated using the Fisher z-transform. Dashed lines show the order of execution of the inspiratory threshold loads.