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Facial muscle activities are essential for the appearance and communication of human beings. Therefore, exploring the activation patterns of facial muscles can help understand facial neuromuscular disorders such as Bell’s palsy. Given the irregular shape of the facial muscles as well as their different locations, it should be difficult to detect the activities of whole facial muscles with a few electrodes. In this study, a high-density surface electromyogram (HD sEMG) system with 90 electrodes was used to record EMG signals of facial muscles in both healthy and Bell’s palsy subjects when they did different facial movements. The electrodes were arranged in rectangular arrays covering the forehead and cheek regions of the face. The muscle activation patterns were shown on maps, which were constructed from the Root Mean Square (RMS) values of all the 90-channel EMG recordings. The experimental results showed that the activation patterns of facial muscles were distinct during doing different facial movements and the activated muscle regions could be clearly observed. Moreover, two features of the activation patterns, 2D correlation coefficient (corr2) and Centre of Gravity (CG) were extracted to quantify the spatial symmetry and the location of activated muscle regions respectively. Furthermore, the deviation of activated muscle regions on the paralyzed side of a face compared to the healthy side was quantified by calculating the distance between two sides of CGs. The results revealed that corr2 of the activated facial muscle region (classified into forehead region and cheek region) in Bell’s palsy subjects was significantly (p < 0.05) lower than that in healthy subjects, while CG distance of activated facial region in Bell’s palsy subjects was significantly (p < 0.05) higher than that in healthy subjects. The correlation between corr2 of these regions and Bell’s palsy [assessed by the Facial Nerve Grading Scale (FNGS) 2.0] was also significant (p < 0.05) in Bell’s palsy subjects. The spatial information on activated muscle regions may be useful in the diagnosis and treatment of Bell’s palsy in the future.

Neural and morphological adaptations combine to underpin the enhanced muscle strength following prolonged exposure to strength training, although their relative importance remains unclear. We investigated the contribution of motor unit (MU) behavior and muscle size to submaximal force production in chronically strength-trained athletes (ST) versus untrained controls (UT). Sixteen ST (age: 22.9 ± 3.5 yr; training experience: 5.9 ± 3.5 yr) and 14 UT (age: 20.4 ± 2.3 yr) performed maximal voluntary isometric force (MViF) and ramp contractions (at 15%, 35%, 50%, and 70% MViF) with elbow flexors, whilst high-density surface electromyography (HDsEMG) was recorded from the biceps brachii (BB). Recruitment thresholds (RTs) and discharge rates (DRs) of MUs identified from the submaximal contractions were assessed. The neural drive-to-muscle gain was estimated from the relation between changes in force (ΔFORCE, i.e. muscle output) relative to changes in MU DR (ΔDR, i.e. neural input). BB maximum anatomical cross-sectional area (ACSA

Introduction: At a professional level, pianists have a high prevalence of playing-related musculoskeletal disorders. This exploratory crossover study was carried out to assess and compare quantitatively [using high density surface electromyography (HDsEMG)], and qualitatively (using musculoskeletal questionnaires) the activity of the lumbar erector spinae muscles (ESM) and the comfort/discomfort in 16 pianists sitting on a standard piano stool (SS) and on an alternative chair (A-chair) with lumbar support and a trunk-thigh angle between 105° and 135°.Materials and Methods: The subjects played for 55 min and HDsEMG was recorded for 20 s every 5 min. For the quantitative assessment of the muscle activity, the spatial mean of the root mean square (RMSROA) and the centroid of the region of activity (ROA) of the ESM were compared between the two chairs. For the qualitative assessment, musculoskeletal questionnaire-based scales were used: General Comfort Rating (GCR); Helander and Zhang’s comfort (HZc) and discomfort (HZd); and Body Part Discomfort (BPD).Results: When using the A-chair, 14 out of 16 pianists (87.5%) showed a significantly lower RMSROA on the left and right side (p < 0.05). The mixed effects model revealed that both chairs (F = 28.21, p < 0.001) and sides (F = 204.01, p < 0.001) contributed to the mean RMSROA variation by subject (Z = 2.64, p = 0.004). GCR comfort indicated that participants found the A-Chair to be “quite comfortable,” and the SS to be “uncomfortable.” GCR discomfort indicated that the SS caused more numbness than the A-Chair (p = 0.05) and indicated the A-Chair to cause more feeling of cramps (p = 0.034). No difference was found on HZc (p = 0.091) or HZd (p = 0.31) between chairs. Female participants (n = 9) reported greater comfort when using the A-Chair than the SS (F = 7.09, p = 0.01) with respect to males. No differences between chairs were indicated by the BPD assessment.Conclusion: It is concluded that using a chair with lumbar support, such as the A-chair, will provide greater comfort, less exertion of the ESM and less discomfort than the standard piano stool.

We investigated whether identification of different finger tasks only relying on the agonist or antagonist extensor digitorum communis (EDC) can be improved by using high-density sEMG (HDsEMG) pre-processed with principal component analysis (PCA). Monopolar HDsEMG was respectively recorded from EDC when the EDC muscle respectively acted as agonist or antagonist muscles. PCA-based approach was evaluated using k-nearest neighbour (KNN) classifier and compared with the classical spatial filters. Using PCA-based configuration can achieve better classification performance in identification of tasks and effort levels and dramatically outperformed spatial filtering configurations in all cases (p

In recent years, many new decomposition methods for identification of motor unit (MU) firings from high-density surface electromyograms (HDEMG) have been developed, with recent attempts focused on the use of different neural networks (NN). In this study, we evaluated the need for HDEMG signal whitening in NN-based MU identification. For this purpose, we analyzed the learning efficiency of two different types of NN, namely dense NN and long short-term memory (LSTM) NN, on the same HDEMG signals, with and without spatial whitening applied to them. All the HDEMG signals used were simulated with advanced HDEMG simulator, providing a full control of MU firing patterns and MU characteristics in our test environment. Spatial whitening of HDEMG signals significantly improved the precision of MU identification, regardless of the type of NN tested. For dense NN, precision of identified MU increased from 32.2 ± 20.2% to 93.1 ± 8.7%, whereas miss rate decreased from 48.4 ± 23.9% to 12.0 ± 13.3% when whitening of HDEMG signals was employed. For LSTM NN the precision of MU identification increased from 59.7 ± 19.7% to 99.4 ± 2.0% whereas miss rate decreased from 43.1 ± 22.3% to 12.7 ± 9.7% with whitening.

The aim of this study was to elucidate the characteristics of the motor unit (MU) firing rate in Charcot-Marie-Tooth disease type 1A (CMT1A) patients and its longitudinal change using high-density surface-electromyography (surface-EMG) and MU decomposition analysis.Nineteen patients with CMT1A and 21 force-matched healthy controls prospectively underwent surface-EMG recording of the vastus lateralis muscle during ramp-up and sustained contractions on performing isometric knee extension. After decomposition analysis, instantaneous firing rates (IFRs) of individually identified MUs were calculated. In CMT1A patients, follow-up measurements were performed one year after the baseline. Comparison of IFRs and clinical variables between CMT1A patients and controls at the baseline and between the baseline and after one year in CMT1A patients was performed.Mean IFRs of MUs were lower in CMT1A patients than in controls. This was true at various force levels in ramp-up contractions (p 0.01. e.g., 10.3 (CMT1A patients) vs. 12.2 (controls) pulses-per-second (pps) at 22.5-27.5% of maximal voluntary contraction (MVC) in MUs recruited at 7.5% of MVC) and at any time-point during sustained contractions (p 0.001. e.g., 8.0 vs. 9.3 pps, respectively, at 10-20 seconds). In CMT1A patients, mean IFRs at 0-10 seconds of sustained contraction were significantly decreased over one year (from 8.06 to 7.52 pps; p = 0.027), whereas the disease severity score and MVC of knee extension did not change over time.CMT1A patients had a lower individual MU firing rate.The MU firing rate is a potential short-term biomarker of axonal damage in CMT1A patients.

Up to 85% of women with interstitial cystitis/bladder pain syndrome have pelvic floor dysfunction and hypertonicity. Current evaluation methodologies lack objective measures of pelvic floor muscle activity. We examined the ability of using intravaginal high-density surface electromyography to quantitatively, objectively and noninvasively map pelvic floor muscle activity and innervation zone locations in patients with interstitial cystitis/bladder pain syndrome.Fifteen women with interstitial cystitis/bladder pain syndrome and 15 controls underwent 2 sessions of digital pelvic examinations and high-density surface electromyography assessments. The root mean squared amplitude of high-density surface electromyography was first calculated, and the resting root mean squared ratio was then calculated by normalizing the resting electromyography root mean squared to the peak electromyography amplitude reached during maximum voluntary contraction. Innervation zone distributions were obtained from decomposed high-density surface electromyography signals. The correlation between the root mean squared ratio and interstitial cystitis/bladder pain syndrome symptom scores and pelvic floor muscle alignment were investigated in patients with interstitial cystitis/bladder pain syndrome and healthy controls.Women with interstitial cystitis/bladder pain syndrome demonstrated significantly increased resting root mean squared ratios compared to controls (0.155±0.048 vs 0.099±0.041, p=0.0019). Significant correlations were found between resting root mean squared ratio and patient reported pain (rIntravaginal high-density surface electromyography offers an objective and quantitative strategy to noninvasively assess pelvic floor muscle dysfunction in women with interstitial cystitis/bladder pain syndrome. Abundant spatiotemporal muscle activity information captured by high-density surface electromyography allows for mapping innervation zone distributions for major pelvic floor muscles.

© 2019 Anatomical Society This study aimed to investigate the spatial distribution and redistribution of lumbar erector spinae (ES) activity during a lumbar extension endurance task in pain-free participants and how this is modified in people with low back pain (LBP). High density surface electromyography (HDEMG) was recorded using 13 × 5 electrode grids placed over the lumbar ES in 13 LBP and 13 control participants while completing an Ito test to task failure. The root mean square of the HDEMG signals was computed, a topographical map of the EMG amplitude generated and the centre of the activity (centroid) determined throughout the task. The centroid of the EMG amplitude map was systematically more cranial (F = 6.09, P = 0.022) for the LBP participants compared with the control subjects. Regression analysis showed that the extent of redistribution of ES activity was associated with longer endurance. These results show that LBP participants utilised a different motor strategy to perform the endurance task, characterised by greater activation of more cranial regions of the ES and less redistribution of ES activity throughout the task. This study provides new insight into the functional activation of the lumbar ES and how it is modified when people have pain.

This pilot study presents a novel application of high density surface electromyography (EMG) decomposition in pediatric patients, with a view toward promoting its potential clinical application for examination of pediatric neuromuscular diseases. Automatic progressive FastICA peel-off (APFP) framework was used to decompose high density surface EMG signals recorded from the first dorsal interosseous and abductor pollicis brevis muscles of children with spinal muscular atrophy. The performance of the decomposition with reduced EMG recording channels was also investigated. In total 131 motor units were extracted from 15 trials of 64-channel (8 ​× ​8) surface EMG. The decomposition yield reduced to 102 motor units when 36-channel (6 ​× ​6) was used, among which 84 motor units were common ones with an average matching rate of (95.68 ​± ​5.26) %. The decomposition yield further reduced to 65 motor units when only 16-channel (4 ​× ​4) was used, among which 57 were common ones with an average matching rate of (95.99 ​± ​4.56) %. These results indicate that using the APFP framework single motor unit activity can be reliably and automatically extracted from pediatric surface EMG signals recorded by an electrode array, which can facilitate potential clinical application of surface EMG as an alternative or supplement to invasive needle EMG for examination of neuromuscular diseases in children.

Objective. It is of great value to accurately localize innervation zones (IZs) to better diagnose and treat neuromuscular diseases, but it is challenging to do so noninvasively from surface electromyography (sEMG) recordings because of the blurring/distorting effect of the low conductive fat tissues. This study aimed to develop an innovative transcutaneous IZ imaging (TIZI) technique to precisely and efficiently localize the IZ distribution directly over the muscle surface in vivo from high-density sEMG recordings (HD-sEMG). Approach. The TIZI technique was implemented by incorporating HD-sEMG recording, signal decomposition, finite element analysis and inverse calculation. The performance of TIZI was evaluated on the flexor digitorum superficialis (FDS) muscle with simulated sEMG signal and experimental signal recorded from both healthy (n = 3) and stroke participants (n = 4). The accuracy of imaging was validated by both of the Pearson correlation coefficient (PCC) and localization error (LE) between the TIZI results and the ‘true’ IZ distribution. Main results. In the simulation study, results have shown PCCs of 99.85% ± 0.11%, 99.79% ± 0.08%, 99.63% ± 0.22% and 99.31% ± 0.54% at the depth of 10, 15, 20 and 25 mm and SNR of 25 dB. PCCs of 98.74% ± 1.78% and 97.82% ± 1.20% were respectively obtained for experimental signals acquired from the healthy and spastic FDS muscles. The TIZI provided smaller LEs of 1.4 ± 0.92 mm and 2.02 ± 1.3 mm, compared to LEs of 7.42 ± 2.29 mm and 7.8 ± 1.77 mm from skin observations in healthy and spastic FDS, respectively. Significance. Results have demonstrated the high performance of the proposed TIZI technique by transcutaneous imaging of the IZ distribution of the skeletal muscles. The performance improvement can be attributed to the elimination of the blurring/distorting effect caused by the low conductive fat and high conductive skin tissues. TIZI may provide an advanced neurological tool for the clinical treatment of neuromuscular diseases, such as guiding botulinum neurotoxin injections in spasticity management.

Acute changes in central control and peripheral properties of motor units following a half-marathon has never been examined in master athletes. Therefore, the main purpose of this study was to estimate the firing properties and twitch characteristics of motor units after a 21-km race in a group of ten trained older adults. High-density surface EMG decomposition was used to identify motor unit activity during a submaximal contraction of the tibialis anterior muscle before and after the half marathon. The area of the estimated motor unit twitch profile was found smaller after the race (P = 0.039). This reduction in contractile efficiency was compensated by a significant increase in the initial and average discharge rate of the identified motor units (P 0.001). By estimating the amount of shared and independent synaptic input to tibialis anterior motor neurons, we demonstrated that adaptations in the discharge properties of master athletes' motor units are the likely consequence of an increased net excitatory synaptic drive to the motor neuron pool. These findings suggest a potential role of long-distance running in ameliorating declines in muscle function of older adults by enhancing the neural drive to muscle.

In this study, we proposed a multi-muscle contraction force estimation framework and implemented it on the elbow flexion task to explore the contributions of different muscles to integrated force at different force levels. High density surface electromyography (HD-sEMG) signals were collected from four muscle groups and the wrist pulling force was measured synchronously. The deep belief network (DBN) was adopted to establish the relationship between HD-sEMG and force. The representative signals of four primary areas, which were considered as the input signal of the force estimation model, were extracted from HD-sEMG by principle component analysis (PCA) algorithm, then fed separately or in common to the DBN to estimate the generated force. And the contributions of different muscle groups to the generated force was analyzed with an index called mean impact value (MIV). The experimental result demonstrates that in multi-muscle contraction task, not all muscles are suitable for force estimation, the force estimation accuracy obtained using only one muscle approximates even exceeds that obtained using multiple muscles, and the relative contributions of different muscle groups to the force can be obtained according to the ranking of MIVs. This scheme provides an effective method for muscle force estimation in multi-muscle contraction tasks, and can be further applied to biomechanics, sports and rehabilitation medicine.

Trunk-movement involves coordinated activity of different lumbar muscles. By assessing the lumbar muscles activity, the pathogeny of some neuromuscular disease might be revealed. Surface electromyography (sEMG) could be used to measure the muscle activity, but for assessing lumbar muscles coordinated activity, there lacks of an accurate and comprehensive application of sEMG. High-density (HD) sEMG provides a potential to assess lumbar muscles coordinated activity more accurately. Thus, in this pilot study, the objective was to assess the lumbar muscles coordinated activity based on HD sEMG. By placing a 5×15 array (75 channels) of HD sEMG electrodes to the surface of the low back area, the sEMG signal from four healthy subjects could be collected. In order to analyze the lumbar muscles coordinated activity, the sEMG signal during different trunk-movements was recorded. Through calculating the root-mean-square (RMS) of each channel and interpolating the RMS value between channels, the sEMG topography could be obtained. The high activity area in the topography showed a regular distribution during different trunk-movements. It might be useful for further assessment of lumbar disease such as low back pain.

Objective: The aim of this study is to compare the performance of three strategies in determining the global innervation zone (IZ) distribution. Methods: High-density surface electromyography was recorded from the biceps brachii muscle of seven healthy subjects under isometric voluntary contractions at 20%, 50%, and 100% of the maximal voluntary contraction and supramaximal musculocutaneous nerve stimulations. IZs were detected: first, by visual identification in a column-specific manner ( IZ-1D ); second, based on decomposed bipolar mapping of motor unit action potentials ( IZ-2D ); and third, by source imaging in the three-dimensional muscle space ( IZ-3D ). Results: All three IZ detection approaches have exhibited excellent trial-to-trial repeatability. Consistent IZ results were found in the axial direction of the arm across all three approaches, yet a difference was observed in the mediolateral direction. Conclusions: Among all three approaches, IZ-3D is capable of providing the most comprehensive information regarding the global IZ distribution, while maintaining high consistency with IZ-1D and IZ-2D results. Significance: IZ-3D approach can be a potential tool for global IZ imaging, which is critical to the clinical diagnosis and treatment of neuromuscular disorders.

Key points Classic motor unit (MU) recording and analysis methods do not allow the same MUs to be tracked across different experimental sessions, and therefore, there is limited experimental evidence on the adjustments in MU properties following training or during the progression of neuromuscular disorders. We propose a new processing method to track the same MUs across experimental sessions (separated by weeks) by using high-density surface electromyography. The application of the proposed method in two experiments showed that individual MUs can be identified reliably in measurements separated by weeks and that changes in properties of the tracked MUs across experimental sessions can be identified with high sensitivity. These results indicate that the behaviour and properties of the same MUs can be monitored across multiple testing sessions. The proposed method opens new possibilities in the understanding of adjustments in motor unit properties due to training interventions or the progression of pathologies. Abstract A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high-density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre–post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra-class correlation coefficients ranged between 0.63—0.99 and 0.39–0.95, respectively). In Experiment II, ∼40% of the MUs could be tracked before and after the training intervention and training-induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders.

Introduction: The objective of this study was to determine whether motor evoked potentials (MEPs) elicited with transcranial magnetic stimulation and measured with conventional bipolar electromyography (EMG) are influenced by crosstalk from non-target muscles. Methods: MEPs were recorded in healthy participants using conventional EMG electrodes placed over the extensor carpi radialis muscle (ECR) and high-density surface EMG (HDsEMG). Fifty MEPs at 120% resting and active motor threshold were recorded. To determine the contribution of ECR to the MEPs, the amplitude distribution across HDsEMG channels was correlated with EMG activity recorded during a wrist extension task. Results: While the conventional EMG identified MEPs from ECR in >90% of the stimulations, HDsEMG revealed that spatial amplitude distribution representative of ECR activation was observed less frequently at rest than while holding a contraction (P

Despite the high prevalence of low back pain (LBP) in rowers, there are few studies investigating changes in lumbar muscle activation in rowers with a recent history of LBP. Such knowledge is relevant to understand potential mechanisms contributing to the maintenance and recurrence of LBP in rowers. For the first time, we evaluate the spatial distribution of erector spinae (ES) activity in rowers with and without a recent history of LBP, using a novel application of high-density surface electromyography (HDEMG).Cross-sectional study.Asymptomatic rowers (N=10) and rowers with a recent history of LBP (N=8) performed 7×4-min exercise bouts (rowing ergometer) until volitional exhaustion. HDEMG signals were acquired bilaterally over the lumbar ES and the root mean square (RMS) amplitude and entropy were analyzed. In addition, the y-axis coordinate of the barycentre (RMS-map) was used to assess changes in ES spatial activation.As the load increased, rowers with LBP showed higher amplitude (p0.01) and less complexity (entropy) of the HDEMG signals (p0.001). In addition, rowers with LBP showed opposite displacements of the barycentre, specifically showing a caudal shift of muscle activity at high intensities (p0.001).Both the magnitude of activation and distribution of ES activity were altered in rowers with a recent history of LBP. The lower complexity of signals together with the caudal displacements of the barycentre suggest an inefficient recruitment of the ES as the load progressed. Modification of the rowing technique in conjunction with feedback from HDEMG might prove useful in future studies.

Phonation is generated by sequentially closing and opening of vocal folds, which is controlled by the laryngeal musculature. Pitch that is the highest contributor to generate natural voice depends on the contraction of muscles over the neck. Proper evaluation of muscular activities from neck muscles would be helpful to understand the phonation functions. While surface electromyography (sEMG) technique has been chosen to investigate physiological characteristics of neck muscles for pitch estimation in previous studies, it remains unclear what are the contracting patterns on both left and right sides of the neck muscles. In this study, 80 channels of high-density (HD) sEMG electrodes were recorded from three healthy volunteers when they phonated vowel (/a/) during varying pitch from normal to high. The root mean square (RMS) of the HD sEMG signals was computed within a series of analysis windows. An averaged RMS was used to construct HD sEMG energy maps for offering average energy distribution of the neck muscles. Normalized RMS (NRMS) was calculated to quantitatively display the correlation of the neck muscles between the left and right sides. The results of sEMG waveforms and NRMS values showed obvious symmetry between the left and right sides of the front neck muscles. Additionally, the NRMS across all five rows revealed a left-right significant correlation (r=0.9432 ± 0.018, p

OBJECTIVES/HYPOTHESIS Laryngeal muscle activation is a complex and dynamic process. Current evaluation methods include needle and surface electromyography (sEMG). Limitations of needle electromyography include patient discomfort, interpretive complexity, and limited duration of recording. sEMG demonstrates interpretive challenges given loss of spatial selectivity. Application of high-density sEMG (HD sEMG) arrays were evaluated for potential to compensate for spatial selectivity loss while retaining benefits of noninvasive monitoring. STUDY DESIGN Basic science. METHODS Ten adults performed phonatory tasks while a 20-channel array recorded spatiotemporal data of the anterior neck. Data were processed to provide average spectral power of each electrode. Comparison was made between rest, low-, and high-pitch phonation. Two-dimensional (2D) spectral energy maps were created to evaluate use in gross identification of muscle location. RESULTS Three phonatory tasks yielded spectral power measures across the HD sEMG array. Each electrode within the array demonstrated unique power values across all subjects (P < .001). Comparison of each electrode to itself across phonatory tasks yielded differences in all subjects during rest versus low versus high, rest versus low, and rest versus high and in 9/10 subjects (P < .001) for low versus high phonation. Symmetry of HD sEMG signal was noted. Review of 2D coronal energy maps allowed for gross identification of cricothyroid muscle amidst anterior strap musculature. CONCLUSIONS HD sEMG can be used to identify differences in anterior neck muscle activity between rest, low-, and high-pitch phonation. HD sEMG of the anterior neck holds potential to enhance diagnostic and therapeutic monitoring for pathologies of laryngeal function. LEVEL OF EVIDENCE NA Laryngoscope, 129:2347-2353, 2019.

INTRODUCTION We investigated the effect of workload and the use of pedal straps on the spatial distribution of neuromuscular activation within the rectus femoris (RF) muscle during pedaling movements. METHODS Eleven healthy men performed submaximal pedaling exercises on an electrically braked ergometer at different workloads and with or without pedal straps. During these tasks, surface electromyograms (SEMGs) were recorded from the RF using 36 electrode pairs, and central locus activation (CLA) was calculated along the longitudinal line of the muscle. RESULTS CLA moved markedly, indicating changes in spatial distribution of SEMG within the muscle, during a crank cycle under all conditions (P

Introduction Due to their complex anatomy, the general activation of lumbar muscles can be estimated with surface electromyography (sEMG) while intramuscular EMG is recommended to isolate information from different back muscles. Whether high-density sEMG recordings can represent the contribution of individual lumbar muscles, as identified with indwelling EMG, needs to be investigated. Material and methods Muscle activity from the right longissimus (L1 and L4) and deep and superficial multifidus (L4) was recorded in eleven participants using fine-wire electrodes during isometric trunk flexions at 20-degrees. We positioned a 13 × 5 electrodes grid over the right lumbar region (L1 to L4) to record sEMG. We used cross-correlations between non-rectified signals from indwelling and sEMG. The spatial location was determined as the medio-lateral and cranio-caudal coordinates of the centroid of the electrodes exhibiting the highest cross-correlation values. To establish an automated approach to identify the spatial distribution of sEMG recordings, we used the independent component analysis (ICA). Results On the sEMG, the centroid of multifidus activity identified with indwelling EMG was medial to that representing longissimus (P Conclusion The spatial distribution of sEMG amplitude provides information on the activation of individual lumbar muscles. Automated EMG decomposition approaches are useful to identify the distinct contribution of individual lumbar muscles using sEMG.

We investigated the possibility to identify motor units (MUs) with high-density surface electromyography (HDEMG) over experimental sessions in different days. 10 subjects performed submaximal knee extensions across three sessions in three days separated by one week, while EMG was recorded from the vastus medialis muscle with high-density electrode grids. The shapes of the MU action potentials (MUAPs) over multiple channels extracted from HDEMG decomposition were matched across sessions by cross-correlation. Forty and twenty percent of the MUs decomposed could be tracked across two and three sessions, respectively (average cross correlation 0.85 ± 0.04). The estimated properties of the matched motor units were similar across the sessions. For example, mean discharge rate and recruitment thresholds were measured with an intra-class correlation coefficient (ICCs) >0.80. These results strongly suggest that the same MUs were indeed identified across sessions. This possibility will allow monitoring changes in MU properties following interventions or during the progression of neuromuscular disorders.

The purpose of this work is to evaluate the effect of the electrode size on recorded High Density surface electromyography (HDsEMG) maps. We recorded the sEMG signals using a grid of electrodes (16 × 8) placed on biceps brachii (5 mm inter electrode distance, IED). Each instantaneous map was interpolated using the 2D Sinc function to obtain a “continuous” map (CM, with 10,000 samp/m). To simulate acquisition with different electrode sizes, each CM was filtered with a circular averaging filter (2–10 mm diameter) and re-sampled with 10 mm IED. Inverse transfer function to compensate the effect of electrode size was applied on each map. The results suggest that greater electrode size implies higher error of power (RMS2) of each map values with respect to the CM. The error of power estimation introduced by electrode size is smaller than the error due to IED.

As sport becomes more competitive, the importance of physical training assessment increases. This paper proposes a new method based on fuzzy analysis techniques for comparing images of muscle activity attained by employing high-density surface electromyography (sEMG). Along with other evaluation techniques, the proposed method could be useful to monitor the evolution of sportsmen's physical training. High-density sEMG maps were generated from sEMG signals acquired from the vastus medialis muscle of the right leg of healthy subjects. The fuzzy logic assessment method has two input variables: the muscle activation area and the mean intensity of muscle activity. Results are displayed on a graphical interface and the method was implemented as a modular, distributed application. The obtained results highlight important differences among sEMG images without pointing out the underlying physiological mechanisms. Future investigations regarding the applicability of the proposed method for long training cycles could provide crucial information about the changes in muscle activity that occur with physical exercise.

Objective. The study of motor unit behavior has been classically performed by selective recording systems of muscle electrical activity (EMG signals) and decomposition algorithms able to discriminate between individual motor unit action potentials from multi-unit signals. In this study, we provide a general framework for the decomposition of multi-channel intramuscular and surface EMG signals and we extensively validate this approach with experimental recordings. Approach. First, we describe the conditions under which the assumptions of the convolutive blind separation model are satisfied. Second, we propose an approach of convolutive sphering of the observations followed by an iterative extraction of the sources. This approach is then validated using intramuscular signals recorded by novel multi-channel thin-film electrodes on the Abductor Digiti Minimi of the hand and Tibilias Anterior muscles, as well as on high-density surface EMG signals recorded by electrode grids on the First Dorsal Interosseous muscle. The validation was based on the comparison with the gold standard of manual decomposition (for intramuscular recordings) and on the two-source method (for comparison of intramuscular and surface EMG recordings) for the three human muscles and contraction forces of up to 90% MVC. Main results. The average number of common sources identified for the validation was 14 ± 7 (averaged across all trials and subjects and all comparisons), with a rate of agreement in their discharge timings of 92.8 ± 3.2%. The average Decomposability Index, calculated on the automatic decomposed signals, was 16.0 ± 2.2 (7.3–44.1). For comparison, the same index calculated on the manual decomposed signals was 15.0 ± 3.0 (6.3–76.6). Significance. These results show that the method provides a solid framework for the decomposition of multi-channel invasive and non-invasive EMG signals that allows the study of the behavior of a large number of concurrently active motor units.

The reliability of triceps surae electromyographic responses to standing perturbations in people after stroke and healthy controls is unknown. High-Density surface Electromyography (HDsEMG) is a technique that records electromyographic signals from different locations over a muscle, overcoming limitations of traditional surface EMG such as between-day differences in electrode placement. In this study, HDsEMG was used to measure responses from soleus (SOL, 18 channels) and medial and lateral gastrocnemius (MG and LG, 16 channels each) in 10 people after stroke and 10 controls. Timing and amplitude of the response were estimated for each channel of the grids. Intraclass Correlation Coefficient (ICC) and normalized Standard Error of Measurement (SEM%) were calculated for each channel individually (single-channel configuration) and on the median of each grid (all-channels configuration). Both timing (single-channel: ICC=0.75-0.96, SEM%=5.0-9.1; all-channels: ICC=0.85-0.97; SEM%=3.5-6.2%) and amplitude (single-channel: ICC=0.60-0.91, SEM%=25.1-46.6; ICC=0.73-0.95, SEM%=19.3-42.1) showed good-to-excellent reliability. HDsEMG provides reliable estimates of EMG responses to perturbations both in individuals after stroke and in healthy controls; reliability was marginally better for the all-channels compared to the single-channel configuration.

Entre las secuelas de lesiones del Sistema Nervioso Central se encuentra la espasticidad, la cual es de dificil manejo terapeutico. Los tratamientos actuales de la espasticidad consideran la administracion de la toxina botulinica. Sin embargo, los resultados de su aplicacion han sido muy variables en terminos de eficacia, atribuible a las distintas distancias entre el lugar de inyeccion y la zona de inervacion (ZI). La EMG de alta densidad se ha utilizado para recolectar informacion acerca de la fisiologia muscular y para localizar la ZI. El objetivo de este estudio fue describir la ubicacion de la ZI del musculo biceps braquial en sujetos jovenes sanos, durante una contraccion isometrica. Evaluamos el musculo biceps braquial en 20 sujetos sanos usando una matriz de 64 electrodos. El promedio de localizacion de la ZI fue de 34% en el sentido distal de la linea trazada entre la fosa cubital y el acromion anterior.

High Density surface Electromyography (HDsEMG) has been applied in both research and clinical applications for non-invasive neuromuscular assessment in several different fields using 2-D array. Proper interpretation of HDsEMG signals requires identifying “good” channels (where there is no short-circuit or bad-contact or major power line interference problem). Recording with many channels usually implies bad-contacts (that introduces large power line interference) and short-circuits (when using gels). In addition to online monitoring the electrode-contact quality, it is necessary to identify “bad” channels, or outliers, prior to the analysis of HDsEMG signal. In this paper we introduce a robust method to identify outliers in a set of monopolar HDsEMG signals recorded from Biceps and Triceps Brachii,Anconeus, Brachioradialis and Pronator Teres. The sensitivity and precision of this method show that this approach is promising.