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Navarro-Sune X, Hudson AL, Fallani FDV, Martinerie J, Witon A, Pouget P, Raux M, Similowski T, Chavez M. Riemannian Geometry Applied to Detection of Respiratory States From EEG Signals: The Basis for a Brain–Ventilator Interface. IEEE Trans Biomed Eng 2017; 64:1138-1148. [DOI: 10.1109/tbme.2016.2592820] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Hudson AL, Navarro-Sune X, Martinerie J, Pouget P, Raux M, Chavez M, Similowski T. Electroencephalographic detection of respiratory-related cortical activity in humans: from event-related approaches to continuous connectivity evaluation. J Neurophysiol 2016; 115:2214-23. [PMID: 26864771 DOI: 10.1152/jn.01058.2015] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Accepted: 02/03/2016] [Indexed: 11/22/2022] Open
Abstract
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.
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Affiliation(s)
- Anna L Hudson
- Neuroscience Research Australia and University of New South Wales, Sydney, Australia;
| | - Xavier Navarro-Sune
- Sorbonne Universités, Université Pierre et Marie Curie, University of Paris 06, Institut National de la Santé et de la Recherche Médicale, UMRS1158 Neurophysiologie Respiratoire Expérimentale et Clinique, Paris, France
| | - Jacques Martinerie
- Centre National de la Recherche Scientifique UMR7225 at the Institut du Cerveau et de la Moelle Épinière, Paris, France
| | - Pierre Pouget
- Centre National de la Recherche Scientifique UMR7225 at the Institut du Cerveau et de la Moelle Épinière, Paris, France
| | - Mathieu Raux
- Sorbonne Universités, Université Pierre et Marie Curie, University of Paris 06, Institut National de la Santé et de la Recherche Médicale, UMRS1158 Neurophysiologie Respiratoire Expérimentale et Clinique, Paris, France; Assistance Publique-Hopitaux de Paris (AP-HP), Groupe Hospitalier Pitie-Salpêtrière-Charles Foix, Département d'Anesthésie-Réanimation, Paris, France; and
| | - Mario Chavez
- Centre National de la Recherche Scientifique UMR7225 at the Institut du Cerveau et de la Moelle Épinière, Paris, France
| | - Thomas Similowski
- Sorbonne Universités, Université Pierre et Marie Curie, University of Paris 06, Institut National de la Santé et de la Recherche Médicale, UMRS1158 Neurophysiologie Respiratoire Expérimentale et Clinique, Paris, France; AP-HP, Groupe Hospitalier Pitie-Salpêtrière-Charles Foix, Service de Pneumologie et Réanimation Medicale, Paris, France
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