Publications

Surface electromyography (sEMG) can be used to measure the electrical activity of the respiratory muscles. The possible applications of sEMG span from patients suffering from acute respiratory failure to patients receiving chronic home mechanical ventilation, to evaluate muscle function, titrate ventilatory support and guide treatment. However, sEMG is mainly used as a monitoring tool for research and its use in clinical practice is still limited-in part due to a lack of standardization and transparent reporting. During this round table meeting, recommendations on data acquisition, processing, interpretation, and potential clinical applications of respiratory sEMG were discussed. This paper informs the clinical researcher interested in respiratory muscle monitoring about the current state of the art on sEMG, knowledge gaps and potential future applications for patients with respiratory failure.

JTD Keywords: Acute respiratory failure, Artificial ventilation, Asthmatic-children, Breathing muscle, Clinical monitoring, Clinical practice, Clinical research, Consensus development, Data interpretation, Disease exacerbation, Drive, Electrode positioning, Electrode removal, Electromyography, Force, Home care, Human, Human diaphragm, Humans, Information processing, Inspiratory muscle training, Inspiratory muscles, Intensive care unit, Knowledge gap, Long term care, Mechanical ventilation, Medical procedures, Muscle contraction, Muscle fatigue, Muscle function, Muscle training, Muscle, skeletal, Muscle-activity, Noninvasive ventilation, Patient monitoring, Patient-ventilator asynchrony, Physiology, Prognosis, Quality of life, Reporting and data system, Respiratory failure, Respiratory muscles, Review, Severe exacerbations, Signal processing, Skeletal muscle, Standardization, Surface electromyography, Time factor

This study explored the use of parasternal second intercostal space and lower intercostal space surface electromyogram (sEMG) and surface mechanomyogram (sMMG) recordings (sEMGpara and sMMGpara, and sEMGlic and sMMGlic, respectively) to assess neural respiratory drive (NRD), neuromechanical (NMC) and neuroventilatory (NVC) coupling, and mechanical efficiency (MEff) noninvasively in healthy subjects and chronic obstructive pulmonary disease (COPD) patients. sEMGpara, sMMGpara, sEMGlic, sMMGlic, mouth pressure (Pmo), and volume (Vi) were measured at rest, and during an inspiratory loading protocol, in 16 COPD patients (8 moderate and 8 severe) and 9 healthy subjects. Myographic signals were analyzed using fixed sample entropy and normalized to their largest values (fSEsEMGpara%max, fSEsMMGpara%max, fSEsEMGlic%max, and fSEsMMGlic%max). fSEsMMGpara%max, fSEsEMGpara%max, and fSEsEMGlic%max were significantly higher in COPD than in healthy participants at rest. Parasternal intercostal muscle NMC was significantly higher in healthy than in COPD participants at rest, but not during threshold loading. Pmo-derived NMC and MEff ratios were lower in severe patients than in mild patients or healthy subjects during threshold loading, but differences were not consistently significant. During resting breathing and threshold loading, Vi-derived NVC and MEff ratios were significantly lower in severe patients than in mild patients or healthy subjects. sMMG is a potential noninvasive alternative to sEMG for assessing NRD in COPD. The ratios of Pmo and Vi to sMMG and sEMG measurements provide wholly noninvasive NMC, NVC, and MEff indices that are sensitive to impaired respiratory mechanics in COPD and are therefore of potential value to assess disease severity in clinical practice. Author

JTD Keywords: biomedical measurement, chronic obstructive pulmonary disease, couplings, diaphragm, disease severity, efficiency, electromyography, exacerbations, healthy volunteers, inspiratory muscles, loading, mechanomyography, obstructive pulmonary-disease, pressure measurement, protocols, respiratory mechanics, respiratory muscles, responsiveness, spirometry, stimulation, volume measurement, At rests, Biomedical measurement, Biomedical measurements, Chronic obstructive pulmonary disease, Couplings, Disease severity, Efficiency ratio, Electromyography, Healthy subjects, Healthy volunteers, Loading, Mechanical efficiency, Mechanomyogram, Muscle, Muscles, Neural respiratory drive, Noninvasive medical procedures, Pressure measurement, Protocols, Pulmonary diseases, Surface electromyogram, Volume measurement

Fixed sample entropy (fSampEn) is a promising technique for the analysis of respiratory electromyographic (EMG) signals. Its use has shown outperformance of amplitude-based estimators such as the root mean square (RMS) in the evaluation of respiratory EMG signals with cardiac noise and a high correlation with respiratory signals, allowing changes in respiratory muscle activity to be tracked. However, the relationship between the fSampEn response to a given muscle activation has not been investigated. The aim of this study was to analyze the nature of the fSampEn measurements that are produced as the EMG activity increases linearly. Simulated EMG signals were generated and increased linearly. The effect of the parameters r and the size of the moving window N of the fSampEn were evaluated and compared with those obtained using the RMS. The RMS showed a linear trend throughout the study. A non-linear, sigmoidal-like behavior was found when analyzing the EMG signals using the fSampEn. The lower the values of r, the higher the non-linearity observed in the fSampEn results. Greater moving windows reduced the variation produced by too small values of r.Clinical Relevance - Understanding the inherent non-linear relationship produced when using the fSampEn in EMG recordings will contribute to the improvement of the respiratory muscle activation assessment at different levels of respiratory effort in patients with respiratory conditions, particularly during the inspiratory phase © 2021 IEEE.

JTD Keywords: Breathing muscle, Breathing rate, Electromyography, Entropy, Heart, Human, Humans, Respiratory muscles, Respiratory rate

Objective. Impaired trunk stability is frequent in spinal cord injury (SCI), but there is a lack of quantitative measures for assessing trunk function. Our objectives were to: (a) evaluate trunk muscle activity and movement patterns during a reaching task in SCI patients, (b) compare the impact of cervical (cSCI) and thoracic (tSCI) injuries in trunk function, and (c) investigate the effects of a startling acoustic stimulus (SAS) in these patients. Approach. Electromyographic (EMG) and smartphone accelerometer data were recorded from 15 cSCI patients, nine tSCI patients, and 24 healthy controls, during a reaching task requiring trunk tilting. We calculated the response time (RespT) until pressing a target button, EMG onset latencies and amplitudes, and trunk tilt, lateral deviation, and other movement features from accelerometry. Statistical analysis was applied to analyze the effects of group (cSCI, tSCI, control) and condition (SAS, non-SAS) in each outcome measure. Main results. SCI patients, especially those with cSCI, presented significantly longer RespT and EMG onset latencies than controls. Moreover, in SCI patients, forward trunk tilt was accompanied by significant lateral deviation. RespT and EMG latencies were remarkably shortened by the SAS (the so-called StartReact effect) in tSCI patients and controls, but not in cSCI patients, who also showed higher variability. Significance. The combination of EMG and smartphone accelerometer data can provide quantitative measures for the assessment of trunk function in SCI. Our results show deficits in postural control and compensatory strategies employed by SCI patients, including delayed responses and higher lateral deviations, possibly to improve sitting balance. This is the first study investigating the StartReact responses in trunk muscles in SCI patients and shows that the SAS significantly accelerates RespT in tSCI, but not in cSCI, suggesting an increased cortical control exerted by these patients.

JTD Keywords: accelerometer, electromyography, impairment, individuals, movements, postural stability, reaction-time, reliability, sitting balance, smartphone, spinal cord injury, startle, startreact, strategies, stroke, trunk, Accelerometer, Electromyography, Sitting balance, Smartphone, Spinal cord injury, Startreact, Trunk

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This study aims to investigate noninvasive indices of neuromechanical coupling (NMC) and mechanical efficiency (MEff) of parasternal intercostal muscles. Gold standard assessment of diaphragm NMC requires using invasive techniques, limiting the utility of this procedure. Nonin-vasive NMC indices of parasternal intercostal muscles can be calculated using surface mechano-myography (sMMGpara) and electromyography (sEMGpara). However, the use of sMMGpara as an in-spiratory muscle mechanical output measure, and the relationships between sMMGpara, sEMGpara, and simultaneous invasive and noninvasive pressure measurements have not previously been eval-uated. sEMGpara, sMMGpara, and both invasive and noninvasive measurements of pressures were recorded in twelve healthy subjects during an inspiratory loading protocol. The ratios of sMMGpara to sEMGpara, which provided muscle-specific noninvasive NMC indices of parasternal intercostal muscles, showed nonsignificant changes with increasing load, since the relationships between sMMGpara and sEMGpara were linear (R2 = 0.85 (0.75–0.9)). The ratios of mouth pressure (Pmo) to sEMGpara and sMMGpara were also proposed as noninvasive indices of parasternal intercostal muscle NMC and MEff, respectively. These indices, similar to the analogous indices calculated using invasive transdiaphragmatic and esophageal pressures, showed nonsignificant changes during threshold loading, since the relationships between Pmo and both sEMGpara (R2 = 0.84 (0.77–0.93)) and sMMGpara (R2 = 0.89 (0.85–0.91)) were linear. The proposed noninvasive NMC and MEff indices of parasternal intercostal muscles may be of potential clinical value, particularly for the regular assessment of patients with disordered respiratory mechanics using noninvasive wearable and wireless devices.

JTD Keywords: inspiratory threshold loading, neuromechanical coupling, parasternal intercostal muscles, respiratory pressure, surface electromyography, surface mechanomyography, Inspiratory threshold loading, Neuromechanical coupling, Parasternal intercostal mus-cles, Respiratory pressure, Surface electromyography, Surface mechanomyography

© 1964-2012 IEEE. 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.

JTD Keywords: atmospheric measurements, concentric ring electrodes, electrocardiography, electrodes, electromyography, laplacian potential, non-invasive respiratory monitoring, particle measurements, respiratory muscles, surface electromyography, Concentric ring electrodes, Laplacian potential, Muscles, Non-invasive respiratory monitoring, Respiratory muscles, Surface electromyography

Reaching and grasping (R&G) is a skilled voluntary movement which is critical for animals. In this work, we aim to identify muscle synergy patterns from R&G movements in rats and show how these patterns can be used to characterize such movements and investigate their consistency and repeatability. For that purpose, we analyzed the electromyographic (EMG) activity of five forelimb muscles recorded while the animals were engaged in R&G tasks. Our dataset included 200 R&G attempts from three different rats. Non-negative matrix factorization was used to decompose EMG signals and extract muscle synergies. We compared all pairs of attempts and created cross-validated models to study intra- and inter-subject variability. We found that three synergies were enough to accurately reconstruct the EMG envelopes. These muscle synergies and their corresponding activation coefficients were very similar for all the attempts in the database, providing a general pattern to describe the movement. Results suggested that the movement strategy adopted by an individual in its different attempts was highly repetitive, but also resembled the strategies adopted by the other animals. Inter-subject variability was not much higher than intra-subject variability. This study is a proof-of-concept, but the proposed approaches can help to establish whether there is a stereotyped pattern of neuromuscular activity in R&G movement in healthy rats, and the changes that occur in animal models of acute neurological injuries. Research on muscle synergies could elucidate motor control mechanisms, and lead to quantitative tools for evaluating upper limb motor impairment after an injury.

JTD Keywords: Electromyography, Motor control, Muscle synergies, Reaching and grasping, Upper limb

Neural respiratory drive as measured by the electromyography allows the study of the imbalance between the load on respiratory muscles and its capacity. Surface respiratory electromyography (sEMG) is a non-invasive tool used for indirectly assessment of NRD. It also provides a way to evaluate the level and pattern of respiratory muscle activation. The prevalence of electrocardiographic activity (ECG) in respiratory sEMG signals hinders its proper evaluation. Moreover, the occurrence of abnormal heartbeats or cardiac arrhythmias in respiratory sEMG measures can make even more challenging the NRD estimation. Respiratory sEMG can be evaluated using the fixed sample entropy (fSampEn), a technique which is less affected by cardiac artefacts. The aim of this work was to investigate the performance of the fSampEn, the root mean square (RMS) and the average rectified value (ARV) on respiratory sEMG signals with supraventricular arrhythmias (SVA) for NRD estimation. fSampEn, ARV and RMS parameters increased as the inspiratory load increased during the test. fSampEn was less influenced by ECG with SVAs for the NRD estimation showing a greater response to respiratory sEMG, reflected with a higher percentage increase with increasing load (228 % total increase, compared to 142 % and 135 % for ARV and RMS, respectively).

JTD Keywords: Electrocardiography, Muscles, Electrodes, Estimation, Band-pass filters, Electromyography, Heart beat

The use of wearable devices in clinical routines could reduce healthcare costs and improve the quality of assessment in patients with chronic respiratory diseases. The purpose of this study is to evaluate the capacity of a Shimmer3 wearable device to extract reliable cardiorespiratory parameters from surface diaphragm electromyography (EMGdi). Twenty healthy volunteers underwent an incremental load respiratory test whilst EMGdi was recorded with a Shimmer3 wearable device (EMGdiW). Simultaneously, a second EMGdi (EMGdiL), inspiratory mouth pressure (Pmouth) and lead-I electrocardiogram (ECG) were recorded via a standard wired laboratory acquisition system. Different cardiorespiratory parameters were extracted from both EMGdiW and EMGdiL signals: heart rate, respiratory rate, respiratory muscle activity and mean frequency of EMGdi signals. Alongside these, similar parameters were also extracted from reference signals (Pmouth and ECG). High correlations were found between the data extracted from the EMGdiW and the reference signal data: heart rate (R = 0.947), respiratory rate (R = 0.940), respiratory muscle activity (R = 0.877), and mean frequency (R = 0.895). Moreover, similar increments in EMGdiW and EMGdiL activity were observed when Pmouth was raised, enabling the study of respiratory muscle activation. In summary, the Shimmer3 device is a promising and cost-effective solution for the ambulatory monitoring of respiratory muscle function in chronic respiratory diseases.

JTD Keywords: Cardiorespiratory monitoring, Chronic respiratory diseases, Fixed sample entropy, Non-invasive respiratory monitoring, Surface diaphragm electromyography, Wearable wireless device

Diaphragm neuromechanical coupling (NMC), which reflects the efficiency of conversion of neural activation to transdiaphragmatic pressure (Pdi), is increasingly recognized to be a useful clinical index of diaphragm function and respiratory mechanics in neuromuscular weakness and cardiorespiratory disease. However, the current gold standard assessment of diaphragm NMC requires invasive measurements of Pdi and crural diaphragm electromyography (oesEMGdi), which complicates the measurement of diaphragm NMC in clinical practice. This is the first study to compare invasive measurements of diaphragm NMC (iNMC) using the relationship between Pdi and oesEMGdi, with noninvasive assessment of NMC (nNMC) using surface mechanomyography (sMMGlic) and electromyography (sEMGlic) of lower chest wall inspiratory muscles. Both invasive and noninvasive measurements were recorded in twelve healthy adult subjects during an inspiratory threshold loading protocol. A linear relationship between noninvasive sMMGlic and sEMGlic measurements was found, resulting in little change in nNMC with increasing inspiratory load. By contrast, a curvilinear relationship between invasive Pdi and oesEMGdi measurements was observed, such that there was a progressive increase in iNMC with increasing inspiratory threshold load. Progressive recruitment of lower ribcage muscles, serving to enhance the mechanical advantage of the diaphragm, may explain the more linear relationship between sMMGlic and sEMGlic (both representing lower intercostal plus costal diaphragm activity) than between Pdi and crural oesEMGdi. Noninvasive indices of NMC derived from sEMGlic and sMMGlic may prove to be useful indices of lower chest wall inspiratory muscle NMC, particularly in settings that do not have access to invasive measures of diaphragm function.

JTD Keywords: Cardiovascular system, Diaphragms, Diseases, Electromyography, Medical signal processing, Neurophysiology, Patient monitoring, Pneumodynamics, Inspiratory muscle neuromechanical coupling, Diaphragm neuromechanical coupling, Neural activation, Transdiaphragmatic pressure, Diaphragm function, Respiratory mechanics, Diaphragm NMC, Invasive measurements, Crural diaphragm electromyography, iNMC, Noninvasive assessment, nNMC, Lower chest wall inspiratory muscles, Inspiratory threshold loading protocol, Noninvasive sMMGlic measurements, sEMGlic measurements, oesEMGdi measurements, Inspiratory threshold load, Lower ribcage muscles, Lower intercostal plus costal diaphragm activity, Crural oesEMGdi, Noninvasive indices, sEMGlic sMMGlic, Lower chest wall inspiratory muscle NMC, Surface mechanomyography, Electromyography, Inspiratory threshold loading, Mechanomyography, Neuromechanical coupling, Respiratory muscles

To optimize long-term nocturnal non-invasive ventilation in patients with chronic obstructive pulmonary disease, surface diaphragm electromyography (EMGdi) might be helpful to detect patient-ventilator asynchrony. However, visual analysis is labor-intensive and EMGdi is heavily corrupted by electrocardiographic (ECG) activity. Therefore, we developed an automatic method to detect inspiratory onset from EMGdi envelope using fixed sample entropy (fSE) and a dynamic threshold based on kernel density estimation (KDE). Moreover, we combined fSE with adaptive filtering techniques to reduce ECG interference and improve onset detection. The performance of EMGdi envelopes extracted by applying fSE and fSE with adaptive filtering was compared to the root mean square (RMS)-based envelope provided by the EMG acquisition device. Automatic onset detection accuracy, using these three envelopes, was evaluated through the root mean square error (RMSE) between the automatic and mean visual onsets (made by two observers). The fSE-based method provided lower RMSE, which was reduced from 298 ms to 264 ms when combined with adaptive filtering, compared to 301 ms provided by the RMS-based method. The RMSE was negatively correlated with the proposed EMGdi quality indices. Following further validation, fSE with KDE, combined with adaptive filtering when dealing with low quality EMGdi, indicates promise for detecting the neural onset of respiratory drive.

JTD Keywords: Fixed sample entropy, Adaptive filtering, Root mean square, Diaphragm electromyography, Non-invasive mechanical ventilation, Chronic obstructive pulmonary disease

Fixed sample entropy (fSampEn) has been successfully applied to myographic signals for inspiratory muscle activity estimation, attenuating interference from cardiac activity. However, several values have been suggested for fSampEn parameters depending on the application, and there is no consensus standard for optimum values. This study aimed to perform a thorough evaluation of the performance of the most relevant fSampEn parameters in myographic respiratory signals, and to propose, for the first time, a set of optimal general fSampEn parameters for a proper estimation of inspiratory muscle activity. Different combinations of fSampEn parameters were used to calculate fSampEn in both non-invasive and the gold standard invasive myographic respiratory signals. All signals were recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing, thus allowing the performance of fSampEn to be evaluated for a variety of inspiratory muscle activation levels. The performance of fSampEn was assessed by means of the cross-covariance of fSampEn time-series and both mouth and transdiaphragmatic pressures generated by inspiratory muscles. A set of optimal general fSampEn parameters was proposed, allowing fSampEn of different subjects to be compared and contributing to improving the assessment of inspiratory muscle activity in health and disease.

JTD Keywords: Electromyography, Fixed sample entropy, Mechanomyography, Non-invasive physiological measurements, Oesophageal electromyography, Respiratory muscle

EMG signals reflect the neuromuscular activation patterns related to the execution of a certain movement or task. In this work, we focus on reaching and grasping (R&G) movements in rats. Our objective is to develop an automatic algorithm to detect the onsets and offsets of muscle activity and use it to study muscle latencies in R&G maneuvers. We had a dataset of intramuscular EMG signals containing 51 R&G attempts from 2 different animals. Simultaneous video recordings were used for segmentation and comparison. We developed an automatic onset/offset detector based on the ratio of local maxima of Teager-Kaiser Energy (TKE). Then, we applied it to compute muscle latencies and other features related to the muscle activation pattern during R&G cycles. The automatic onsets that we found were consistent with visual inspection and video labels. Despite the variability between attempts and animals, the two rats shared a sequential pattern of muscle activations. Statistical tests confirmed the differences between the latencies of the studied muscles during R&G tasks. This work provides an automatic tool to detect EMG onsets and offsets and conducts a preliminary characterization of muscle activation during R&G movements in rats. This kind of approaches and data processing algorithms can facilitate the studies on upper limb motor control and motor impairment after spinal cord injury or stroke.

JTD Keywords: Muscles, Electromyography, Rats, Low pass filters, Microsoft Windows, Band-pass filters

Fixed sample entropy (fSampEn) is a robust technique that allows the evaluation of inspiratory effort in diaphragm electromyography (EMGdi) signals, and has potential utility in sleep studies. To appropriately estimate respiratory effort, fSampEn requires the adjustment of several parameters. The aims of the present study were to evaluate the influence of the embedding dimension m, the tolerance value r, the size of the moving window, and the sampling frequency, and to establish recommendations for estimating the respiratory activity when using the fSampEn on surface EMGdi recorded for different inspiratory efforts. Values of m equal to 1 and r ranging from 0.1 to 0.64, and m equal to 2 and r ranging from 0.13 to 0.45, were found to be suitable for evaluating respiratory activity. fSampEn was less affected by window size than classical amplitude parameters. Finally, variations in sampling frequency could influence fSampEn results. In conclusion, the findings suggest the potential utility of fSampEn for estimating muscle respiratory effort in further sleep studies.

JTD Keywords: Fixed sample entropy (fSampEn), Non-invasive respiratory monitoring, Respiratory activity, Respiratory effort, Surface diaphragm electromyography

Diaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of neural respiratory drive (NRD). The EMGdi signal is, however, corrupted by electrocardiographic (ECG) activity, and this presence of cardiac activity can make the EMGdi interpretation more difficult. Traditionally, the EMGdi amplitude has been estimated using the average rectified value (ARV) and the root mean square (RMS). In this work, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to traditional ARV and RMS methods. The fSampEn is calculated using a tolerance value fixed and independent of the standard deviation of the analysis window. Thus, this method quantifies the amplitude of the complex components of stochastic signals (such as EMGdi), and being less affected by changes in amplitude due to less complex components (such as ECG). The proposed method was tested in synthetic and recorded EMGdi signals. fSampEn was less sensitive to the effect of cardiac activity on EMGdi signals with different levels of NRD than ARV and RMS amplitude parameters. The mean and standard deviation of the Pearson’s correlation values between inspiratory mouth pressure (an indirect measure of the respiratory muscle activity) and fSampEn, ARV and RMS parameters, estimated in the recorded EMGdi signal at tidal volume (without inspiratory load), were 0.38???0.12, 0.27???0.11 and 0.11???0.13, respectively. Whereas at 33 cmH2O (maximum inspiratory load) were 0.83???0.02, 0.76???0.07 and 0.61???0.19, respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.

JTD Keywords: Electromyography, diaphragm muscle, neural respiratory drive

Extracting clinical information from one single measurement represents a step forward in the assessment of the respiratory muscle function. This attracting idea entails the reduction of the instrumentation and fosters to develop new medical integrated technologies. We present the use of the fixed sample entropy (fSampEn) as a more direct method to non-invasively derive the breathing activity from the diaphragm electromyographic (EMGdi) signal, and thus to extract the respiratory rate, an important vital sign which is cumbersome and time-consuming to be measured by clinicians. fSampEn is a method to evaluate the EMGdi activity that is less sensitive to the cardiac activity (ECG) and its application has proven to be useful to evaluate the load of the respiratory muscles. The behavior of the proposed method was tested in signals from two subjects that performed an inspiratory load protocol, which consists of increments in the inspiratory mouth pressure (P_mouth). Two respiratory signals were derived and compared to the P_mouth signal: the ECG-derived respiration (EDR) signal from the lead-I configuration, and the EMG-derived respiration (EMGDR) signal by applying the fSampEn method over the EMGdi signal. The similitude and the lag between signals were calculated through the cross-correlation between each derived respiratory signal and the P_mouth. The EMGDR signal showed higher correlation and lower lag values (≥ 0.91 and ≤ 0.70 s, respectively) than the EDR signal (≥ 0.83 and ≤0.99 s, respectively). Additionally, the respiratory rate was estimated with the P_mouth, EDR and EMGDR signals showing very similar values. The results from this preliminary work suggest that the fSampEn method can be used to derive the respiration waveform from the respiratory muscle electrical activity.

JTD Keywords: Band-pass filters, Electrocardiography, Electromyography, Entropy, Mouth, Muscles, Protocols

Stroke is a leading cause of adult disability with upper-limb hemiparesis being one of the most frequent consequences. Given that stroke only affects the paretic arm's control structure (the set of synergies and activation vectors needed to perform a movement), we propose that the control structure of the non-affected arm can serve as a physiological reference to rehabilitate the paretic arm. However, it is unclear how rehabilitation can effectively tune the control structure of a patient. The use of Visual Feedback (VF) is recommended to boost stroke rehabilitation, as it is able to positively modify neural mechanisms and improve motor performance. Thus, in this study we investigate whether VF can effectively modify the control structure of the upper-limb. We asked six neurologically intact subjects to perform a complete upper-limb rehabilitation routine comprised of 12 movements in absence and presence of VF. Our results indicate that VF significantly increases interlimb similarity both in terms of synergies and activation coefficients. However, the magnitude of improvement depended upon each subject. In general, VF brings the control structure of the nondominant side closer to the control structure of dominant side, suggesting that VF modifies the control structure towards more optimized motor patterns. This is especially interesting because stroke mainly affects the activation coefficients of patients and because it has been shown that the control of the affected side resembles that of the nondominant side. In conclusion, VF may enhance motor performance by effectively tuning the control-structure. Notably, this finding offers new insights to design improved stroke rehabilitation.

JTD Keywords: Bars, Biomedical engineering, Electrodes, Electromyography, Mirrors, Muscles, Visualization

The poor rehabilitation success rate, including the cases of ineffective and detrimental adaptations, make stroke a leading cause of disability. Thus, it is essential to recognize the mechanisms driving healthy motor recovery to improve such rate. Stroke alters the Synergy Architecture (SA), the modular muscle control system. So SA analysis may constitute a powerful tool to design and assess rehabilitation procedures. However, current impairment scales do not consider the patient's neuromuscular state. To gain insights into this hypothesis, we recorded multiple myoelectric signals from upper-limb muscles, in healthy subjects, while executing a set of common rehabilitation exercises. We found that SA reveals optimized motor control strategies and the positive effects of the use of visual feedback (VF) on motor control. Furthermore we demonstrate that the right and left arm's SA share the basic structure within the same subject, so we propose using the unaffected limb's SA as a reference motion pattern to be reached through rehabilitation.

JTD Keywords: Bars, Electromyography, Motor drives, Neuromuscular, Vectors, Visualization

Diaphragm electromyography (EMGdi) provides important information on diaphragm activity, to detect neuromuscular disorders of the most important muscle in the breathing inspiratory phase. EMGdi is habitually recorded using needles or esophageal catheters, with the implication of being invasive for patients. Surface electrodes offer an alternative for the non-invasive assessment of diaphragm activity. Ag/AgCl surface disc electrodes are used in monopolar or bipolar configuration to record EMGdi signals. On the other hand, Laplacian surface potential can be estimated by signal recording through active concentric ring electrodes. This kind of recording could reduce physiological interferences, increase the spatial selectivity and reduce orientation problems in the electrode location. The aim of this work is to compare EMGdi signals recorded simultaneously with disc electrodes in bipolar configuration and a Laplacian ring electrode over chest wall. EMGdi signal was recorded in one healthy subject during a breath hold maneuver and a static inspiratory maneuver based on Mueller’s technique. In order to estimate the covered frequency range and the degree of noise contamination in both bipolar and Laplacian EMGdi signals, the cumulative percentage of the power spectrum and the signal to noise ratio in sub-bands were determined. Furthermore, diaphragm fatigue was evaluated by means of amplitude and frequency parameters. Our findings suggest that Laplacian EMGdi recording covers a broader frequency range although with higher noise contamination compared to bipolar EMGdi recording. Finally, in Laplacian recording fatigue indexes showed a clearer trend for muscle fatigue detection and also a reduced cardiac interference, providing an alternative to bipolar recording for diaphragm fatigue studies.

JTD Keywords: Laplacian electrode, Diaphragm muscle, Fatigue, Surface electromyography

The study of the amplitude of respiratory muscle mechanomyographic (MMG) signals could be useful in clinical practice as an alternative non-invasive technique to assess respiratory muscle strength. The MMG signal is stochastic in nature, and its amplitude is usually estimated by means of the average rectified value (ARV) or the root mean square (RMS) of the signal. Both parameters can be used to estimate MMG activity, as they correlate well with muscle force. These estimations are, however, greatly affected by the presence of structured impulsive noise that overlaps in frequency with the MMG signal. In this paper, we present a method for assessing muscle activity based on the Lempel-Ziv algorithm: the Multistate Lempel-Ziv (MLZ) index. The behaviour of the MLZ index was tested with synthesised signals, with various amplitude distributions and degrees of complexity, and with recorded diaphragm MMG signals. We found that this index, like the ARV and RMS parameters, is positively correlated with changes in amplitude of the diaphragm MMG components, but is less affected by components that have non-random behaviour (like structured impulsive noise). Therefore, the MLZ index could provide more information to assess the MMG-force relationship.

JTD Keywords: Diaphragm, Electromyography, Lempel-Ziv, Mechanomyography, Muscle force, Respiratory muscles