Assessing respiratory mechanics and muscle function is critical for both clinical practice and research purposes. Several methodological developments over the past two decades have enhanced our understanding of respiratory muscle function and responses to interventions across the spectrum of health and disease. They are especially useful in diagnosing, phenotyping and assessing treatment efficacy in patients with respiratory symptoms and neuromuscular diseases. Considerable research has been undertaken over the past 17 years, since the publication of the previous American Thoracic Society (ATS)/European Respiratory Society (ERS) statement on respiratory muscle testing in 2002. Key advances have been made in the field of mechanics of breathing, respiratory muscle neurophysiology (electromyography, electroencephalography and transcranial magnetic stimulation) and on respiratory muscle imaging (ultrasound, optoelectronic plethysmography and structured light plethysmography). Accordingly, this ERS task force reviewed the field of respiratory muscle testing in health and disease, with particular reference to data obtained since the previous ATS/ERS statement. It summarises the most recent scientific and methodological developments regarding respiratory mechanics and respiratory muscle assessment by addressing the validity, precision, reproducibility, prognostic value and responsiveness to interventions of various methods. A particular emphasis is placed on assessment during exercise, which is a useful condition to stress the respiratory system.

The presence of a respiratory-related cortical activity during tidal breathing is abnormal and a hallmark of respiratory difficulties, but its detection requires superior discrimination and temporal resolution. The aim of this study was to validate a computational method using EEG covariance (or connectivity) matrices to detect a change in brain activity related to breathing. In 17 healthy subjects, EEG was recorded during resting unloaded breathing (RB), voluntary sniffs, and breathing against an inspiratory threshold load (ITL). EEG were analyzed by the specially developed covariance-based classifier, event-related potentials, and time-frequency (T-F) distributions. Nine subjects repeated the protocol. The classifier could accurately detect ITL and sniffs compared with the reference period of RB. For ITL, EEG-based detection was superior to airflow-based detection (P < 0.05). A coincident improvement in EEG-airflow correlation in ITL compared with RB (P < 0.05) confirmed that EEG detection relates to breathing. Premotor potential incidence was significantly higher before inspiration in sniffs and ITL compared with RB (P < 0.05), but T-F distributions revealed a significant difference between sniffs and RB only (P< 0.05). Intraclass correlation values ranged from poor (-0.2) to excellent (1.0). Thus, as for conventional event-related potential analysis, the covariance-based classifier can accurately predict a change in brain state related to a change in respiratory state, and given its capacity for near "real-time" detection, it is suitable to monitor the respiratory state in respiratory and critically ill patients in the development of a brain-ventilator interface.

BackgroundCongenital central hypoventilation syndrome (CCHS) is a rare neuro-respiratory disorder associated with mutations of the PHOX2B gene. Patients with this disease experience severe hypoventilation during sleep and are consequently ventilator-dependent. However, they breathe almost normally while awake, indicating the existence of cortical mechanisms compensating for the deficient brainstem generation of automatic breathing. Current evidence indicates that the supplementary motor area plays an important role in modulating ventilation in awake normal humans. We hypothesized that the wake-related maintenance of spontaneous breathing in patients with CCHS could involve supplementary motor area.MethodsWe studied 7 CCHS patients (5 women; age: 20–30; BMI: 22.1±4 kg.m−2) during resting breathing and during exposure to carbon dioxide and inspiratory mechanical constraints. They were compared with 8 healthy individuals. Segments of electroencephalographic tracings were selected according to ventilatory flow signal, from 2.5 seconds to 1.5 seconds after the onset of inspiration. After artefact rejection, 80 or more such segments were ensemble averaged. A slow upward shift of the EEG signal starting between 2 and 0.5 s before inspiration (pre-inspiratory potential) was considered suggestive of supplementary motor area activation.ResultsIn the control group, pre-inspiratory potentials were generally absent during resting breathing and carbon dioxide stimulation, and consistently identified in the presence of inspiratory constraints (expected). In CCHS patients, pre-inspiratory potentials were systematically identified in all study conditions, including resting breathing. They were therefore significantly more frequent than in controls.ConclusionsThis study provides a neurophysiological substrate to the wakefulness drive to breathe that is characteristic of CCHS and suggests that the supplementary motor area contributes to this phenomenon. Whether or not this “cortical breathing” can be taken advantage of therapeutically, or has clinical consequences (like competition with attentional resources) remains to be determined.