A Multichannel EMG System for Spatial Measurement of Diaphragm Activities

• Published in: IEEE sensors journal Vol. 22; no. 23; pp. 23393 - 23402
• Main Authors: Kusche, Roman, Grashoff, Jan, Oltmann, Andra, Rostalski, Philipp
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Belts; Diaphragm (anatomy); diaphragmatic electromyography (EMGdi); Digital computers; Digital signal processing; Digitization; Dry electrodes; electrical activity of the diaphragm (EAdi); Electrical measurement; electrode belt; Electrodes; Electromyography; Frequency measurement; measurement system; Modular systems; multichannel; Muscles; Personal computers; Propagation; Rehabilitation; respiration monitoring; Robustness; Signal processing; spatiotemporal electromyography (EMG); Thorax; Three dimensional models; Ventilation; Ventilators
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2022.3213868

An important aspect of mechanical ventilation is the recognition and quantification of spontaneous respiratory effort. However, a measurement of flows and pressures often used for this purpose is prone to error. A promising alternative is to detect diaphragmatic contractions, directly. A method recently proposed is to acquire the diaphragm electromyography (EMG) signals using surface electrodes. However, this method is often limited by disturbances and electrode placements for some applications in which the patient is moving, such as rehabilitation or breathing training. In this work, we present a novel noninvasive method that addresses these problems. This method is based on a novel dry electrode belt, which can be used to comfortably derive EMG signals from the thorax, in combination with a developed electrical measurement system. The modular multichannel system is capable of simultaneously deriving and digitizing 32 differential EMG channels and sending them to a personal computer (PC). A specific digital signal processing chain allows combining the data into one robust overall signal. In addition, the signals derived from the thorax can be used to obtain information regarding the spatiotemporal propagation of the diaphragm EMG. To verify the functionality, the system is characterized. Subsequently, subject measurements are performed. From these, the spatiotemporal propagation of diaphragm EMG on the thorax can be identified. For better visualization, this propagation is graphically displayed in a 3-D model. In addition, it is shown how the combination of all signals can be used to obtain a robust overall signal that can be used to control ventilators.