Evaluation of Respiratory Muscle Activity by Means of Concentric Ring Electrodes

Surface electromyography (sEMG) can be used for the evaluation of respiratory muscle activity. Recording sEMG involves the use of surface electrodes in a bipolar configuration. However, electrocardiographic (ECG) interference and electrode orientation represent considerable drawbacks to bipolar acquisition. As an alternative, concentric ring electrodes (CREs) can be used for sEMG acquisition and offer great potential for the evaluation of respiratory muscle activity due to their enhanced spatial resolution and simple placement protocol, which does not depend on muscle fiber orientation. The aim of this work was to analyze the performance of CREs during respiratory sEMG acquisitions. Respiratory muscle sEMG was applied to the diaphragm and sternocleidomastoid muscles using a bipolar and a CRE configuration. Thirty-two subjects underwent four inspiratory load spontaneous breathing tests which was repeated after interchanging the electrode positions. We calculated parameters such as (1) spectral power and (2) median frequency during inspiration, and power ratios of inspiratory sEMG without ECG in relation to (3) basal sEMG without ECG (Rins/noise), (4) basal sEMG with ECG (Rins/cardio) and (5) expiratory sEMG without ECG (Rins/exp). Spectral power, Rins/noise and Rins/cardio increased with the inspiratory load. Significantly higher values (p < 0.05) of Rins/cardio and significantly higher median frequencies were obtained for CREs. Rins/noise and Rins/exp were higher for the bipolar configuration only in diaphragm sEMG recordings, whereas no significant differences were found in the sternocleidomastoid recordings. Our results suggest that the evaluation of respiratory muscle activity by means of sEMG can benefit from the remarkably reduced influence of cardiac activity, the enhanced detection of the shift in frequency content and the axial isotropy of CREs which facilitates its placement.

[1]  Raimon Jané,et al.  Influence of Parameter Selection in Fixed Sample Entropy of Surface Diaphragm Electromyography for Estimating Respiratory Activity , 2017, Entropy.

[2]  Stephen C-Y Lu,et al.  Active Laplacian Electrode for The Data-acquisition System of EHG , 2005 .

[3]  G. Prats-Boluda,et al.  Enhancement of Non-Invasive Recording of Electroenterogram by Means of a Flexible Array of Concentric Ring Electrodes , 2013, Annals of Biomedical Engineering.

[4]  G. Prats-Boluda,et al.  Towards the clinical use of concentric electrodes in ECG recordings: influence of ring dimensions and electrode position , 2016 .

[5]  José Antonio Fiz,et al.  Study of myographic signals from sternomastoid muscle in patients with chronic obstructive pulmonary disease , 2000, IEEE Transactions on Biomedical Engineering.

[6]  Peter P. Tarjan,et al.  Pasteless, Active, Concentric Ring Sensors for Directly Obtained Laplacian Cardiac Electrograms , 2002 .

[7]  R Merletti,et al.  Location of innervation zones of sternocleidomastoid and scalene muscles – a basis for clinical and research electromyography applications , 2002, Clinical Neurophysiology.

[8]  C. Mantilla,et al.  Non-stationarity and power spectral shifts in EMG activity reflect motor unit recruitment in rat diaphragm muscle , 2013, Respiratory Physiology & Neurobiology.

[9]  M. Polkey,et al.  ERS statement on respiratory muscle testing at rest and during exercise , 2019, European Respiratory Journal.

[10]  G. Prats-Boluda,et al.  Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics. , 2013, Medical engineering & physics.

[11]  J Moxham,et al.  Neural respiratory drive in healthy subjects and in COPD , 2008, European Respiratory Journal.

[12]  Raimon Jané,et al.  Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy , 2016, IEEE Journal of Biomedical and Health Informatics.

[13]  R Bloch Subtraction of electrocardiographic signal from respiratory electromyogram. , 1983, Journal of applied physiology: respiratory, environmental and exercise physiology.

[14]  A. Lopes Advances in spirometry testing for lung function analysis , 2019, Expert review of respiratory medicine.

[15]  Raimon Jané,et al.  Characterization of laplacian surface electromyographic signals during isometric contraction in biceps brachii , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[16]  M. Mizuno,et al.  Human respiratory muscles: fibre morphology and capillary supply. , 1991, The European respiratory journal.

[17]  Yiyao Ye-Lin,et al.  Wireless sensor node for non-invasive high precision electrocardiographic signal acquisition based on a multi-ring electrode , 2017 .

[18]  Javier Garcia-Casado,et al.  Feasibility and Analysis of Bipolar Concentric Recording of Electrohysterogram with Flexible Active Electrode , 2014, Annals of Biomedical Engineering.

[19]  Carlo J. De Luca,et al.  The Use of Surface Electromyography in Biomechanics , 1997 .

[20]  Eduardo García-Breijo,et al.  A Flexible Multiring Concentric Electrode for Non-Invasive Identification of Intestinal Slow Waves , 2018, Sensors.

[21]  Raimon Jané,et al.  Noninvasive Assessment of Inspiratory Muscle Neuromechanical Coupling During Inspiratory Threshold Loading , 2019, IEEE Access.

[22]  J. Martin,et al.  Effects of inspiratory loading on respiratory muscle activity during expiration. , 2015, The American review of respiratory disease.

[23]  L Finsen,et al.  Intramuscular and surface EMG power spectrum from dynamic and static contractions. , 1995, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[24]  W. Besio,et al.  Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping , 2007, Physiological measurement.

[25]  L. V. van Eykern,et al.  Reproducibility and responsiveness of a noninvasive EMG technique of the respiratory muscles in COPD patients and in healthy subjects. , 2004, Journal of applied physiology.

[26]  A. Sheel,et al.  Diaphragm Recruitment Increases during a Bout of Targeted Inspiratory Muscle Training. , 2016, Medicine and science in sports and exercise.

[27]  George S. Moschytz,et al.  Low-pass filter effect in the measurement of surface EMG , 1997, Proceedings of Computer Based Medical Systems.

[28]  Yuichi Nakamura,et al.  Motion estimation of five fingers using small concentric ring electrodes for measuring surface electromyography , 2014, 2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE).

[29]  Raimon Jané,et al.  Evaluation of a Wearable Device to Determine Cardiorespiratory Parameters From Surface Diaphragm Electromyography , 2019, IEEE Journal of Biomedical and Health Informatics.

[30]  Gema Prats-Boluda,et al.  Assessment of Respiratory Muscle Activity with Surface Electromyographic Signals Acquired by Concentric Ring Electrodes , 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[31]  R. Cohen,et al.  Body surface Laplacian ECG mapping , 1992, IEEE Transactions on Biomedical Engineering.

[32]  High-frequency oscillation and centroid frequency of diaphragm EMG during inspiratory loading. , 1998, Respiration physiology.

[33]  L. B. Januario,et al.  Surface electromyography in inspiratory muscles in adults and elderly individuals: A systematic review. , 2019, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[34]  Raimon Jané,et al.  Electromyography-Based Respiratory Onset Detection in COPD Patients on Non-Invasive Mechanical Ventilation , 2019, Entropy.

[35]  L. V. van Eykern,et al.  Respiratory muscle EMG in newborns: a non-intrusive method. , 1977, Early human development.

[36]  Oleksandr Makeyev,et al.  High-Frequency Oscillations Recorded on the Scalp of Patients With Epilepsy Using Tripolar Concentric Ring Electrodes , 2014, IEEE Journal of Translational Engineering in Health and Medicine.

[37]  B. Freriks,et al.  Development of recommendations for SEMG sensors and sensor placement procedures. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[38]  M. Johnson,et al.  Data on the distribution of fibre types in thirty-six human muscles. An autopsy study. , 1973, Journal of the neurological sciences.

[39]  Peter Holland,et al.  Removing ECG noise from surface EMG signals using adaptive filtering , 2009, Neuroscience Letters.

[40]  Jack P Callaghan,et al.  Elimination of electrocardiogram contamination from electromyogram signals: An evaluation of currently used removal techniques. , 2006, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[41]  M. Estenne,et al.  Neck muscle activity in patients with severe chronic obstructive pulmonary disease. , 1994, American journal of respiratory and critical care medicine.

[42]  Alberto Rainoldi,et al.  Innervation zone locations in 43 superficial muscles: Toward a standardization of electrode positioning , 2014, Muscle & nerve.

[43]  C. Amorim,et al.  Inspiratory muscular activation during threshold therapy in elderly healthy and patients with COPD. , 2005, Journal of Electromyography & Kinesiology.

[44]  Dario Farina,et al.  Concentric-ring electrode systems for noninvasive detection of single motor unit activity , 2001, IEEE Transactions on Biomedical Engineering.

[45]  Walter G. Besio,et al.  Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes , 2007, Journal of Neuroscience Methods.

[46]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[47]  B. He,et al.  Estimation of Noise Level and Signal to Noise Ratio of Laplacian Electrocardiogram During Ventricular Depolarization and Repolarization , 2002, Pacing and clinical electrophysiology : PACE.

[48]  Tse Nga Ng,et al.  Stretchable Dry Electrodes with Concentric Ring Geometry for Enhancing Spatial Resolution in Electrophysiology , 2017, Advanced healthcare materials.

[49]  Javier Garcia-Casado,et al.  Time-frequency representations of the sternocleidomastoid muscle electromyographic signal recorded with concentric ring electrodes , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).