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University Hospital Leuven

1 ARTICLES PUBLISHED IN JoVE

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Medicine

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
Antenor Rodrigues 1,2, Luc Janssens 3,4, Daniel Langer 4,5, Umi Matsumura 6, Dmitry Rozenberg 7,8, Laurent Brochard 1,2, W. Darlene Reid 2,9,10
1Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, Unity Health Toronto, 2Interdepartmental Division of Critical Care Medicine, University of Toronto, 3Faculty of Engineering Technology, Electrical Engineering, KU Leuven, 4Department of Rehabilitation Sciences, Faculty of Movement and Rehabilitation Sciences, Research Group for Rehabilitation in Internal Disorders, KU Leuven, 5Respiratory Rehabilitation and Respiratory Division, University Hospital Leuven, 6Department of Health Sciences, Nagasaki University Graduate School of Biomedical Sciences, 7Department of Medicine, Temerty Faculty of Medicine, Division of Respirology, University of Toronto, University Health Network, 8Toronto General Hospital Research Institute, University Health Network, 9Department of Physical Therapy, University of Toronto, 10KITE, Toronto Rehabilitation Institute, University Health Network

Here, we describe a protocol to record and analyze respiratory electromyography (EMG) signals. It includes the anatomic references for placing the EMG electrodes over several respiratory muscles, removing electrocardiographic noise from the EMG signals, and acquiring the EMG root mean square (RMS) and onset timing of activity.

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