Respiratory Surface Electromyography: Concepts, Utility, and Challenges

1. Introduction

Electromyography (EMG) involves the acquisition of electrical signals produced by changes in action potentials of muscle units during muscular contraction and relaxation. This recording typically requires the placement of electrodes within or on the surface of the muscles of interest. The former type of EMG recording is invasive while the latter, also known as surface EMG (sEMG), is non-invasive and is generally the preferred mode for clinical purposes as well as for evaluation of exercise performance. The utility of sEMG is well established, and in recent years, its role in the evaluation of respiratory muscles is progressively recognized [1]. The commonest muscles of respiration that are used for respiratory sEMG are the diaphragm (that contributes to about 70% of the force of inspiration in healthy adults), intercostal, sternocleidomastoid, and scalene muscles. The field of respiratory sEMG is rapidly expanding and this chapter is aimed at exploring its role and potential, and the challenges faced in clinical application.

2. Rationale for respiratory sEMG

The respiratory neural drive is the efferent signal generated from the respiratory center to the respiratory muscles during inspiration [2], and this signal is generated in response to the myriad afferent sources that provide feedback to the respiratory control center in the body’s respiratory control system. As illustrated in Figure 1, recording sEMG of respiratory muscles during inspiration provides a non-invasive and contemporaneous measurement of the respiratory neural drive [3]. Evaluating a subject’s respiratory neural drive is important for two main reasons. The first is that it provides an objective and synchronic measure of the level of dyspnea the subject is experiencing. Since it is impossible to measure dyspneic sensation at the higher cortical centers currently, measuring the respiratory neural drive represents the best alternative, as the respiratory neural drive is an exact “copy” of the corollary discharge being sent to the higher cortical centers by the respiratory center after processing all the stimuli from afferent sources [4]. The second indication for measuring respiratory neural drive with respiratory sEMG is to non-invasively determine the intrathoracic pressures generated by the inspiratory pump, Pmus.

3. Current and potential clinical applications of respiratory sEMG

The global prevalence of COPD in 2020 was estimated to be 10.6%, or 480 million cases, and projected to increase to 600 million cases by 2050 [10]. Dyspnea or breathing discomfort and associated exercise limitation are the two most troubling symptoms reported by patients with COPD [11]. Accordingly, current global management guidelines on stable COPD prioritize the reduction of these symptoms as a key treatment goal [12]. However, as asserted in a comprehensive albeit lengthy dissertation on evaluating dyspnea in obstructive lung disease [3], the present methods of measuring dyspnea with questionnaires and symptom scores, i.e., by psychometric evaluation, are inadequate. This is especially so for the purpose of evaluating patient responses to treatments aimed at alleviating dyspnea. The lack of a universally accepted instrument for measuring dyspnea is testament to this inadequacy and the “profusion of measures” currently available, in fact, militates against progress in developing novel therapies for relief of dyspnea. Respiratory sEMG extends physiological assessment of dyspnea with a potential for widespread clinical application.

The health and societal burden inflicted by COPD is enormous, with healthcare resource utilization resulting from exacerbation of COPD accounting for most of the direct and indirect healthcare costs [10]. Clinical studies conducted in separate centers across the globe have found that adding sEMG measurement to current standard evaluation can meliorate the need for hospitalization and predict risk of readmissions following hospital discharge in patients with exacerbation of COPD [13, 14, 15]. COPD exacerbations have often been defined and treated according to clinical symptoms alone and not till recently has the addition of other objective parameters been recommended in grading the severity of such episodes for treatment purposes [12, 16]. The addition of sEMG, if widely available, will likely contribute to the evaluation and treatment of unstable COPD patients in future, as the foregoing clinical trials have shown. The benefits of sEMG can likewise be extended to respiratory monitoring of any case of acute dyspnea. The recent finding of Pmus as the parameter that best predicts success of non-invasive ventilation and high-flow oxygen therapy in patients with COVID-19 infection serves to emphasize the need to measure Pmus, reliably and readily, in conscious patients during acute situations [17]. The recent pandemic has also highlighted the requisition for accurate respiratory assessment of patients on remote telemonitoring [18]. The availability and portability of respiratory surface EMG equipment will undoubtedly contribute to the accuracy of respiratory monitoring in numerous scenarios in future.

In addition to the usefulness of respiratory sEMG based on its amplitude correlation with respiratory neural drive and respiratory effort as explicated above, another functional dimension is the potential of EMG in detecting muscle fatigue [19]. This is made possible by identifying changes in the frequency of EMG signals with the onset of muscle fatigue, thus generating possibilities beyond current capabilities in exercise testing and prescription [3, 20].

A list of the current and potential applications of respiratory surface EMG is presented in Table 1.

4. Challenges in developing respiratory sEMG

The transition of theoretical concepts of respiratory sEMG to practical usage is not straightforward. The technological challenges of sEMG may be classified into two—signal acquisition and signal conditioning [21]. The former requires optimal sensor design and placement, as sEMG signals are generally weak (measured in microvolts) and have high signal-to-noise ratios. This is especially applicable in relation to surface EMG sensors for respiratory muscles like the diaphragm, as high impedance due to overlying tissues and “cross-talk” from surrounding muscles is encountered. sEMG signal processing is correspondingly not a simple matter—signal amplification, noise reduction, and signal interpretation require complex algorithms, especially if precise electromechanical association is desired, e.g., in correlating sEMG signals with respiratory parameters like Pmus, breath flow rate, tidal volume, etc. Further progress is imminent as an important initial step appears to have been set in motion with the recent round-table discussion among interested researchers focusing on standardization and developing best practices in the analysis and applications of respiratory sEMG [22].

5. Conclusion

The use of non-invasive sEMG for the measurement and monitoring of respiratory muscle activity portends a promising new paradigm in the subjective and objective assessment of breathing. The clinical potential of respiratory sEMG in the management of patients with dyspnea, a symptom sine qua non of COPD, is immense.

Conflict of interest

The author declares no conflict of interest.