Journal articles: 'High density surface electromyographic signals'

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Marateb, Hamid R., Monica Rojas-Martínez, Marjan Mansourian, Roberto Merletti, and Miguel A. Mañanas Villanueva. "Outlier detection in high-density surface electromyographic signals." Medical & Biological Engineering & Computing 50, no. 1 (June 23, 2011): 79–89. http://dx.doi.org/10.1007/s11517-011-0790-7.

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Chen, Chen, Shihan Ma, Xinjun Sheng, Dario Farina, and Xiangyang Zhu. "Adaptive Real-Time Identification of Motor Unit Discharges From Non-Stationary High-Density Surface Electromyographic Signals." IEEE Transactions on Biomedical Engineering 67, no. 12 (December 2020): 3501–9. http://dx.doi.org/10.1109/tbme.2020.2989311.

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Song, Rui, Xu Zhang, Xi Chen, Xiang Chen, Xun Chen, Shuang Yang, and Erwei Yin. "Decoding silent speech from high-density surface electromyographic data using transformer." Biomedical Signal Processing and Control 80 (February 2023): 104298. http://dx.doi.org/10.1016/j.bspc.2022.104298.

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Li, Yuchang, Hongqing Pan, and Quanjun Song. "ADS1299-Based Array Surface Electromyography Signal Acquisition System." Journal of Physics: Conference Series 2383, no. 1 (December 1, 2022): 012054. http://dx.doi.org/10.1088/1742-6596/2383/1/012054.

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A multi-channel sEMG signal acquisition system based on the analog front-end chip ADS1299 is designed. The whole acquisition system consists of a 2×9 high-density electrode array, ADS1299 multi-channel high-precision A/D conversion chip; A MCU named STM32F103C8, an upper computer, and PC. We carried out electrode array design, The introduction of the function of the ADS1299 chip, and the circuit design of the analog signal acquisition part. The test results show that the acquisition system designed in this paper can ideally collect the sEMG signal of 8 channels on the back of the hand, which proves the effectiveness of this design in extracting weak EMG signals. Therefore, it has reference significance for designing larger-scale sEMG signal acquisition circuits.

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Sleutjes, B. T. H. M., M. De Vos, J. H. Blok, I. Montfoort, B. Mijović, M. Signoretto, S. Van Huffel, and I. Gligorijević. "Motor Unit Tracking Using High Density Surface Electromyography (HDsEMG)." Methods of Information in Medicine 54, no. 03 (2015): 221–26. http://dx.doi.org/10.3414/me13-02-0049.

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SummaryIntroduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Biosignal Interpretation: Advanced Methods for Neural Signals and Images”.Objectives: The study discusses a technique to automatically correct for effects of electrode grid displacement across serial surface EMG measurements with high-density electrode arrays (HDsEMG). The goal is to match motor unit signatures from subsequent measurements and by this, achieve automated motor unit tracking.Methods: Test recordings of voluntary muscle contractions using HDsEMG were performed on three healthy individuals. Electrode grid displacements were mimicked in repeated recordings while measuring the exact position of the grid. A concept of accounting for translational and rotational displacements by making the projection of the recorded motor unit action potentials is first introduced. Then, this concept was tested for the performed measurements attempting the automated matching of the similar motor unit action potentials across different trials.Results: The ability to perform automated correction (projection) of the isolated motor unit action potentials was first shown using large angular displacements. Then, for accidental (small) displacements of the recording grid, the ability to automatically track motor units across different measurement trials was shown. It was possible to track 10 –15% of identified motor units.Conclusions: This proof of concept study demonstrates an automated correction allowing the identification of an increased number of same motor unit action potentials across different measurements. By this, great potential is demonstrated for assisting motor unit tracking studies, indicating that otherwise electrode displacements cannot always be precisely described.

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Ibrahim, Ayad Assad, Ikhlas Mahmoud Farhan, and Mohammed Ehasn Safi. "A nonlinearities inverse distance weighting spatial interpolation approach applied to the surface electromyography signal." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (April 1, 2022): 1530. http://dx.doi.org/10.11591/ijece.v12i2.pp1530-1539.

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Spatial interpolation of a surface electromyography (sEMG) signal from a set of signals recorded from a multi-electrode array is a challenge in biomedical signal processing. Consequently, it could be useful to increase the electrodes' density in detecting the skeletal muscles' motor units under detection's vacancy. This paper used two types of spatial interpolation methods for estimation: Inverse distance weighted (IDW) and Kriging. Furthermore, a new technique is proposed using a modified nonlinearity formula based on IDW. A set of EMG signals recorded from the noninvasive multi-electrode grid from different types of subjects, sex, age, and type of muscles have been studied when muscles are under regular tension activity. A goodness of fit measure (R2) is used to evaluate the proposed technique. The interpolated signals are compared with the actual signals; the Goodness of fit measure's value is almost 99%, with a processing time of 100msec. The resulting technique is shown to be of high accuracy and matching of spatial interpolated signals to actual signals compared with IDW and Kriging techniques.

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Xue, Suqi, Farong Gao, Xudong Wu, Qun Xu, Xuecheng Weng, and Qizhong Zhang. "MUNIX repeatability evaluation method based on FastICA demixing." Mathematical Biosciences and Engineering 20, no. 9 (2023): 16362–82. http://dx.doi.org/10.3934/mbe.2023730.

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<abstract> <p>To enhance the reproducibility of motor unit number index (MUNIX) for evaluating neurological disease progression, this paper proposes a negative entropy-based fast independent component analysis (FastICA) demixing method to assess MUNIX reproducibility in the presence of inter-channel mixing of electromyography (EMG) signals acquired by high-density electrodes. First, composite surface EMG (sEMG) signals were obtained using high-density surface electrodes. Second, the FastICA algorithm based on negative entropy was employed to determine the orthogonal projection matrix that minimizes the negative entropy of the projected signal and effectively separates mixed sEMG signals. Finally, the proposed experimental approach was validated by introducing an interrelationship criterion to quantify independence between adjacent channel EMG signals, measuring MUNIX repeatability using coefficient of variation (CV), and determining motor unit number and size through MUNIX. Results analysis shows that the inclusion of the full (128) channel sEMG information leads to a reduction in CV value by $1.5 \pm 0.1$ and a linear decline in CV value with an increase in the number of channels. The correlation between adjacent channels in participants decreases by $0.12 \pm 0.05$ as the number of channels gradually increases. The results demonstrate a significant reduction in the number of interrelationships between sEMG signals following negative entropy-based FastICA processing, compared to the mixed sEMG signals. Moreover, this decrease in interrelationships becomes more pronounced with an increasing number of channels. Additionally, the CV of MUNIX gradually decreases with an increase in the number of channels, thereby optimizing the issue of abnormal MUNIX repeatability patterns and further enhancing the reproducibility of MUNIX based on high-density surface EMG signals.</p> </abstract>

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Martinez-Valdes, Eduardo, Francesco Negro, Deborah Falla, Alessandro Marco De Nunzio, and Dario Farina. "Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles." Journal of Applied Physiology 124, no. 4 (April 1, 2018): 1071–79. http://dx.doi.org/10.1152/japplphysiol.01115.2017.

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Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P < 0.001), whereas the EMG amplitude normalized with respect to MVC was greater for VL than VM ( P < 0.04). Because differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P < 0.001), and this difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials. NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.

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Gamucci, Fiorenza, Marcello Pallante, Sybille Molle, Enrico Merlo, and Andrea Bertuglia. "A Preliminary Study on the Use of HD-sEMG for the Functional Imaging of Equine Superficial Muscle Activation during Dynamic Mobilization Exercises." Animals 12, no. 6 (March 20, 2022): 785. http://dx.doi.org/10.3390/ani12060785.

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Superficial skeletal muscle activation is associated with an electric activity. Bidimensional High-Density Surface Electromyography (HD-sEMG) is a non-invasive technique that uses a grid of equally spaced electrodes applied on the skin surface to detect and portray superficial skeletal muscle activation. The goal of the study was to evaluate the feasibility of HD-sEMG to detect electrical activation of skeletal muscle and its application during rehabilitation exercises in horses. To fulfil this aim, activation of the superficial descending pectoral and external abdominal oblique core muscles were measured using HD-sEMG technology during dynamic mobilization exercises to induce lateral bending and flexion/extension tasks of the trunk. Masseter muscle was instrumented during mastication as a control condition. A 64 surface EMG channel wireless system was used with a single 64 electrode grid or a pair of 32 electrode grids. HD-sEMG provided unique information on the muscular activation onset, duration, and offset, along each motor task, and permitting inferences about the motor control strategy actuated by the central nervous system. Signals were further processed to obtain firing frequencies of few motor-neurons. Estimation of electromyographic amplitude and spectral parameters allowed detecting the onset of muscular fatigue during the motor tasks performed. HD-sEMG allows the assessment of muscular activation in horses performing specific motor tasks, supporting its future application in clinical and research settings.

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Hossen, A., G. Deuschl, S. Groppa, U. Heute, and M. Muthuraman. "Discrimination of physiological tremor from pathological tremor using accelerometer and surface EMG signals." Technology and Health Care 28, no. 5 (September 18, 2020): 461–76. http://dx.doi.org/10.3233/thc-191947.

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BACKGROUND AND OBJECTIVE: Although careful clinical examination and medical history are the most important steps towards a diagnostic separation between different tremors, the electro-physiological analysis of the tremor using accelerometry and electromyography (EMG) of the affected limbs are promising tools. METHODS: A soft-decision wavelet-based decomposition technique is applied with 8 decomposition stages to estimate the power spectral density of accelerometer and surface EMG signals (sEMG) sampled at 800 Hz. A discrimination factor between physiological tremor (PH) and pathological tremor, namely, essential tremor (ET) and the tremor caused by Parkinson’s disease (PD), is obtained by summing the power entropy in band 6 (B6: 7.8125–9.375 Hz) and band 11 (B11: 15.625–17.1875 Hz). RESULTS: A discrimination accuracy of 93.87% is obtained between the PH group and the ET & PD group using a voting between three results obtained from the accelerometer signal and two sEMG signals. CONCLUSION: Biomedical signal processing techniques based on high resolution wavelet spectral analysis of accelerometer and sEMG signals are implemented to efficiently perform classification between physiological tremor and pathological tremor.

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Wen, Yue, Simon Avrillon, Julio C. Hernandez-Pavon, Sangjoon J. Kim, François Hug, and José L. Pons. "A convolutional neural network to identify motor units from high-density surface electromyography signals in real time." Journal of Neural Engineering 18, no. 5 (April 6, 2021): 056003. http://dx.doi.org/10.1088/1741-2552/abeead.

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PHINYOMARK, ANGKOON, FRANCK QUAINE, YANN LAURILLAU, SIRINEE THONGPANJA, CHUSAK LIMSAKUL, and PORNCHAI PHUKPATTARANONT. "EMG AMPLITUDE ESTIMATORS BASED ON PROBABILITY DISTRIBUTION FOR MUSCLE–COMPUTER INTERFACE." Fluctuation and Noise Letters 12, no. 03 (September 2013): 1350016. http://dx.doi.org/10.1142/s0219477513500168.

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To develop an advanced muscle–computer interface (MCI) based on surface electromyography (EMG) signal, the amplitude estimations of muscle activities, i.e., root mean square (RMS) and mean absolute value (MAV) are widely used as a convenient and accurate input for a recognition system. Their classification performance is comparable to advanced and high computational time-scale methods, i.e., the wavelet transform. However, the signal-to-noise-ratio (SNR) performance of RMS and MAV depends on a probability density function (PDF) of EMG signals, i.e., Gaussian or Laplacian. The PDF of upper-limb motions associated with EMG signals is still not clear, especially for dynamic muscle contraction. In this paper, the EMG PDF is investigated based on surface EMG recorded during finger, hand, wrist and forearm motions. The results show that on average the experimental EMG PDF is closer to a Laplacian density, particularly for male subject and flexor muscle. For the amplitude estimation, MAV has a higher SNR, defined as the mean feature divided by its fluctuation, than RMS. Due to a same discrimination of RMS and MAV in feature space, MAV is recommended to be used as a suitable EMG amplitude estimator for EMG-based MCIs.

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Campanini, Isabella, Andrea Merlo, Catherine Disselhorst-Klug, Luca Mesin, Silvia Muceli, and Roberto Merletti. "Fundamental Concepts of Bipolar and High-Density Surface EMG Understanding and Teaching for Clinical, Occupational, and Sport Applications: Origin, Detection, and Main Errors." Sensors 22, no. 11 (May 30, 2022): 4150. http://dx.doi.org/10.3390/s22114150.

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Surface electromyography (sEMG) has been the subject of thousands of scientific articles, but many barriers limit its clinical applications. Previous work has indicated that the lack of time, competence, training, and teaching is the main barrier to the clinical application of sEMG. This work follows up and presents a number of analogies, metaphors, and simulations using physical and mathematical models that provide tools for teaching sEMG detection by means of electrode pairs (1D signals) and electrode grids (2D and 3D signals). The basic mechanisms of sEMG generation are summarized and the features of the sensing system (electrode location, size, interelectrode distance, crosstalk, etc.) are illustrated (mostly by animations) with examples that teachers can use. The most common, as well as some potential, applications are illustrated in the areas of signal presentation, gait analysis, the optimal injection of botulinum toxin, neurorehabilitation, ergonomics, obstetrics, occupational medicine, and sport sciences. The work is primarily focused on correct sEMG detection and on crosstalk. Issues related to the clinical transfer of innovations are also discussed, as well as the need for training new clinical and/or technical operators in the field of sEMG.

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Chen, Jiangcheng, Sheng Bi, George Zhang, and Guangzhong Cao. "High-Density Surface EMG-Based Gesture Recognition Using a 3D Convolutional Neural Network." Sensors 20, no. 4 (February 21, 2020): 1201. http://dx.doi.org/10.3390/s20041201.

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High-density surface electromyography (HD-sEMG) and deep learning technology are becoming increasingly used in gesture recognition. Based on electrode grid data, information can be extracted in the form of images that are generated with instant values of multi-channel sEMG signals. In previous studies, image-based, two-dimensional convolutional neural networks (2D CNNs) have been applied in order to recognize patterns in the electrical activity of muscles from an instantaneous image. However, 2D CNNs with 2D kernels are unable to handle a sequence of images that carry information concerning how the instantaneous image evolves with time. This paper presents a 3D CNN with 3D kernels to capture both spatial and temporal structures from sequential sEMG images and investigates its performance on HD-sEMG-based gesture recognition in comparison to the 2D CNN. Extensive experiments were carried out on two benchmark datasets (i.e., CapgMyo DB-a and CSL-HDEMG). The results show that, where the same network architecture is used, 3D CNN can achieve a better performance than 2D CNN, especially for CSL-HDEMG, which contains the dynamic part of finger movement. For CapgMyo DB-a, the accuracy of 3D CNN was 1% higher than 2D CNN when the recognition window length was equal to 40 ms, and was 1.5% higher when equal to 150 ms. For CSL-HDEMG, the accuracies of 3D CNN were 15.3% and 18.6% higher than 2D CNN when the window length was equal to 40 ms and 150 ms, respectively. Furthermore, 3D CNN achieves a competitive performance in comparison to the baseline methods.

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Jaber, Hanadi, Mofeed rashid, and Luigi Fortuna. "Interactive Real-Time Control System for The Artificial Hand." Iraqi Journal for Electrical and Electronic Engineering 16, no. 1 (May 11, 2020): 1–10. http://dx.doi.org/10.37917/ijeee.16.1.8.

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In recent years, the number of researches in the field of artificial limbs has increased significantly in order to improve the performance of the use of these limbs by amputees. During this period, High-Density surface Electromyography (HD-sEMG) signals have been employed for hand gesture identification, in which the performance of the classification process can be improved by using robust spatial features extracted from HD-sEMG signals. In this paper, several algorithms of spatial feature extraction have been proposed to increase the accuracy of the SVM classifier, while the histogram oriented gradient (HOG) has been used to achieve this mission. So, several feature sets have been extracted from HD-sEMG signals such as; features extracted based on HOG denoted by (H); features have been generated by combine intensity feature with H features denoted as (HI); features have been generated by combine average intensity with H features denoted as (AIH). The proposed system has been simulated by MATLAB to calculate the accuracy of the classification process, in addition, the proposed system is practically validated in order to show the ability to use this system by amputees. The results show the high accuracy of the classifier in real-time which leads to an increase in the possibility of using this system as an artificial hand.

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Xu, Qun, Suqi Xue, Farong Gao, Qiuxuan Wu, and Qizhong Zhang. "Evaluation method of motor unit number index based on optimal muscle strength combination." Mathematical Biosciences and Engineering 20, no. 2 (2022): 3854–72. http://dx.doi.org/10.3934/mbe.2023181.

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<abstract> <p>Repeatability is an important attribute of motor unit number index (MUNIX) technology. This paper proposes an optimal contraction force combination for MUNIX calculation in an effort to improve the repeatability of this technology. In this study, the surface electromyography (EMG) signals of the biceps brachii muscle of eight healthy subjects were initially recorded with high-density surface electrodes, and the contraction strength was the maximum voluntary contraction force of nine progressive levels. Then, by traversing and comparing the repeatability of MUNIX under various combinations of contraction force, the optimal combination of muscle strength is determined. Finally, calculate MUNIX using the high-density optimal muscle strength weighted average method. The correlation coefficient and the coefficient of variation are utilized to assess repeatability. The results show that when the muscle strength combination is 10, 20, 50 and 70% of the maximum voluntary contraction force, the repeatability of MUNIX is greatest, and the correlation between MUNIX calculated using this combination of muscle strength and conventional methods is high (PCC > 0.99), the repeatability of the MUNIX method improved by 11.5–23.8%. The results indicate that the repeatability of MUNIX differs for various combinations of muscle strength and that MUNIX, which is measured with a smaller number and lower-level contractility, has greater repeatability.</p> </abstract>

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Cavalcanti, Jéssica D., Guilherme Augusto F. Fregonezi, Antonio J. Sarmento, Thiago Bezerra, Lucien P. Gualdi, Francesca Pennati, Andrea Aliverti, and Vanessa R. Resqueti. "Electrical activity and fatigue of respiratory and locomotor muscles in obstructive respiratory diseases during field walking test." PLOS ONE 17, no. 4 (April 1, 2022): e0266365. http://dx.doi.org/10.1371/journal.pone.0266365.

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Introduction In subjects with obstructive respiratory diseases the increased work of breathing during exercise can trigger greater recruitment and fatigue of respiratory muscles. Associated with these changes, lower limb muscle dysfunctions, further contribute to exercise limitations. We aimed to assess electrical activity and fatigue of two respiratory and one locomotor muscle during Incremental Shuttle Walking Test (ISWT) in individuals with obstructive respiratory diseases and compare with healthy. Methods This is a case-control study. Seventeen individuals with asthma (asthma group) and fifteen with chronic obstructive pulmonary disease (COPD group) were matched with healthy individuals (asthma and COPD control groups). Surface electromyographic (sEMG) activity of sternocleidomastoid (SCM), scalene (ESC), and rectus femoris (RF) were recorded during ISWT. sEMG activity was analyzed in time and frequency domains at baseline and during the test (33%, 66%, and 100% of ISWT total time) to obtain, respectively, signal amplitude and power spectrum density (EMG median frequency [MF], high- and low-frequency bands, and high/low [H/L] ratio). Results Asthma group walked a shorter distance than controls (p = 0.0007). sEMG amplitudes of SCM, ESC, and RF of asthma and COPD groups were higher at 33% and 66% of ISWT compared with controls groups (all p<0.05). SCM and ESC of COPD group remained higher until 100% of the test. MF of ESC and RF decreased in asthma group (p = 0.016 and p < 0.0001, respectively) versus controls, whereas MF of SCM (p < 0.0001) decreased in COPD group compared with controls. H/L ratio of RF decreased (p = 0.002) in COPD group versus controls. Conclusion Reduced performance is accompanied by increased electromyographic activity of SCM and ESC and activation of RF in individuals with obstructive respiratory diseases during ISWT. These are susceptible to be more pronounced respiratory and peripheral muscle fatigue than healthy subjects during exercise.

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Favretto, M. A., S. Cossul, F. R. Andreis, L. R. Nakamura, M. F. Ronsoni, S. Tesfaye, D. Selvarajah, and J. L. B. Marques. "Alterations of tibialis anterior muscle activation pattern in subjects with type 2 diabetes and diabetic peripheral neuropathy." Biomedical Physics & Engineering Express 8, no. 2 (January 5, 2022): 025001. http://dx.doi.org/10.1088/2057-1976/ac455b.

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Abstract Diabetic peripheral neuropathy (DPN) is associated with loss of motor units (MUs), which can cause changes in the activation pattern of muscle fibres. This study investigated the pattern of muscle activation using high-density surface electromyography (HD-sEMG) signals from subjects with type 2 diabetes mellitus (T2DM) and DPN. Thirty-five adults participated in the study: 12 healthy subjects (HV), 12 patients with T2DM without DPN (No-DPN) and 11 patients with T2DM with DPN (DPN). HD-sEMG signals were recorded in the tibialis anterior muscle during an isometric contraction of ankle dorsiflexion at 50% of the maximum voluntary isometric contraction (MVIC) during 30-s. The calculated HD-sEMG signals parameters were the normalised root mean square (RMS), normalised median frequency (MDF), coefficient of variation (CoV) and modified entropy (ME). The RMS increased significantly (p = 0.001) with time only for the DPN group, while the MDF decreased significantly (p < 0.01) with time for the three groups. Moreover, the ME was significantly lower (p = 0.005), and CoV was significantly higher (p = 0.003) for the DPN group than the HV group. Using HD-sEMG, we have demonstrated a reduction in the number of MU recruited by individuals with DPN. This study provides proof of concept for the clinical utility of this technique for identifying neuromuscular impairment caused by DPN.

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Nishikawa, Yuichi, Kohei Watanabe, Aleš Holobar, Tetsuya Takahashi, Noriaki Maeda, Hirofumi Maruyama, Shinobu Tanaka, and Allison S. Hyngstrom. "Association between the Degree of Pre-Synaptic Dopaminergic Pathway Degeneration and Motor Unit Firing Behavior in Parkinson’s Disease Patients." Sensors 21, no. 19 (October 4, 2021): 6615. http://dx.doi.org/10.3390/s21196615.

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The relationship between motor unit (MU) firing behavior and the severity of neurodegeneration in Parkinson’s disease (PD) is not clear. This study aimed to elucidate the association between degeneration with dopaminergic pathways and MU firing behavior in people with PD. Fourteen females with PD (age, 72.6 ± 7.2 years, disease duration, 3.5 ± 2.1 years) were enrolled in this study. All participants performed a submaximal, isometric knee extension ramp-up contraction from 0% to 80% of their maximal voluntary contraction strength. We used high-density surface electromyography with 64 electrodes to record the muscle activity of the vastus lateralis muscle and decomposed the signals with the convolution kernel compensation technique to extract the signals of individual MUs. We calculated the degree of degeneration of the central lesion-specific binding ratio by dopamine transporter single-photon emission computed tomography. The primary, novel results were as follows: (1) moderate-to-strong correlations were observed between the degree of degeneration of the central lesion and MU firing behavior; (2) a moderate correlation was observed between clinical measures of disease severity and MU firing behavior; and (3) the methods of predicting central nervous system degeneration from MU firing behavior abnormalities had a high detection accuracy with an area under the curve >0.83. These findings suggest that abnormalities in MU activity can be used to predict central nervous system degeneration following PD.

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Murphy, Spencer A., Francesco Negro, Dario Farina, Tanya Onushko, Matthew Durand, Sandra K. Hunter, Brian D. Schmit, and Allison Hyngstrom. "Stroke increases ischemia-related decreases in motor unit discharge rates." Journal of Neurophysiology 120, no. 6 (December 1, 2018): 3246–56. http://dx.doi.org/10.1152/jn.00923.2017.

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Following stroke, hyperexcitable sensory pathways, such as the group III/IV afferents that are sensitive to ischemia, may inhibit paretic motor neurons during exercise. We quantified the effects of whole leg ischemia on paretic vastus lateralis motor unit firing rates during submaximal isometric contractions. Ten chronic stroke survivors (>1 yr poststroke) and 10 controls participated. During conditions of whole leg occlusion, the discharge timings of motor units were identified from decomposition of high-density surface electromyography signals during repeated submaximal knee extensor contractions. Quadriceps resting twitch responses and near-infrared spectroscopy measurements of oxygen saturation as an indirect measure of blood flow were made. There was a greater decrease in paretic motor unit discharge rates during the occlusion compared with the controls (average decrease for stroke and controls, 12.3 ± 10.0% and 0.1 ± 12.4%, respectively; P < 0.001). The motor unit recruitment thresholds did not change with the occlusion (stroke: without occlusion, 11.68 ± 5.83%MVC vs. with occlusion, 11.11 ± 5.26%MVC; control: 11.87 ± 5.63 vs. 11.28 ± 5.29%MVC). Resting twitch amplitudes declined similarly for both groups in response to whole leg occlusion (stroke: 29.16 ± 6.88 vs. 25.75 ± 6.78 Nm; control: 38.80 ± 13.23 vs 30.14 ± 9.64 Nm). Controls had a greater exponential decline (lower time constant) in oxygen saturation compared with the stroke group (stroke time constant, 22.90 ± 10.26 min vs. control time constant, 5.46 ± 4.09 min; P < 0.001). Ischemia of the muscle resulted in greater neural inhibition of paretic motor units compared with controls and may contribute to deficient muscle activation poststroke. NEW & NOTEWORTHY Hyperexcitable inhibitory sensory pathways sensitive to ischemia may play a role in deficient motor unit activation post stroke. Using high-density surface electromyography recordings to detect motor unit firing instances, we show that ischemia of the exercising muscle results in greater inhibition of paretic motor unit firing rates compared with controls. These findings are impactful to neurophysiologists and clinicians because they implicate a novel mechanism of force-generating impairment poststroke that likely exacerbates baseline weakness.

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Dideriksen, Jakob L., Ales Holobar, and Deborah Falla. "Preferential distribution of nociceptive input to motoneurons with muscle units in the cranial portion of the upper trapezius muscle." Journal of Neurophysiology 116, no. 2 (August 1, 2016): 611–18. http://dx.doi.org/10.1152/jn.01117.2015.

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Pain is associated with changes in the neural drive to muscles. For the upper trapezius muscle, surface electromyography (EMG) recordings have indicated that acute noxious stimulation in either the cranial or the caudal region of the muscle leads to a relative decrease in muscle activity in the cranial region. It is, however, not known if this adaption reflects different recruitment thresholds of the upper trapezius motor units in the cranial and caudal region or a nonuniform nociceptive input to the motor units of both regions. This study investigated these potential mechanisms by direct motor unit identification. Motor unit activity was investigated with high-density surface EMG signals recorded from the upper trapezius muscle of 12 healthy volunteers during baseline, control (intramuscular injection of isotonic saline), and painful (hypertonic saline) conditions. The EMG was decomposed into individual motor unit spike trains. Motor unit discharge rates decreased significantly from control to pain conditions by 4.0 ± 3.6 pulses/s (pps) in the cranial region but not in the caudal region (1.4 ± 2.8 pps; not significant). These changes were compatible with variations in the synaptic input to the motoneurons of the two regions. These adjustments were observed, irrespective of the location of noxious stimulation. These results strongly indicate that the nociceptive synaptic input is distributed in a nonuniform way across regions of the upper trapezius muscle.

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Huang, Chengjun, Maoqi Chen, Zhiyuan Lu, Cliff S. Klein, and Ping Zhou. "Spatial Dependence of Log-Transformed Electromyography–Force Relation: Model-Based Sensitivity Analysis and Experimental Study of Biceps Brachii." Bioengineering 10, no. 4 (April 12, 2023): 469. http://dx.doi.org/10.3390/bioengineering10040469.

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This study investigated electromyography (EMG)–force relations using both simulated and experimental approaches. A motor neuron pool model was first implemented to simulate EMG–force signals, focusing on three different conditions that test the effects of small or large motor units located more or less superficially in the muscle. It was found that the patterns of the EMG–force relations varied significantly across the simulated conditions, quantified by the slope (b) of the log-transformed EMG-force relation. b was significantly higher for large motor units, which were preferentially located superficially rather than for random depth or deep depth conditions (p < 0.001). The log-transformed EMG–force relations in the biceps brachii muscles of nine healthy subjects were examined using a high-density surface EMG. The slope (b) distribution of the relation across the electrode array showed a spatial dependence; b in the proximal region was significantly larger than the distal region, whereas b was not different between the lateral and medial regions. The findings of this study provide evidence that the log-transformed EMG–force relations are sensitive to different motor unit spatial distributions. The slope (b) of this relation may prove to be a useful adjunct measure in the investigation of muscle or motor unit changes associated with disease, injury, or aging.

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Afsharipour, B., K. Ullah, and R. Merletti. "Amplitude indicators and spatial aliasing in high density surface electromyography recordings." Biomedical Signal Processing and Control 22 (September 2015): 170–79. http://dx.doi.org/10.1016/j.bspc.2015.07.001.

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Gallina, Alessio, Tanya D. Ivanova, and S. Jayne Garland. "Regional activation within the vastus medialis in stimulated and voluntary contractions." Journal of Applied Physiology 121, no. 2 (August 1, 2016): 466–74. http://dx.doi.org/10.1152/japplphysiol.00050.2016.

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This study examined the contribution of muscle fiber orientation at different knee angles to regional activation identified with high-density surface electromyography (HDsEMG). Monopolar HDsEMG signals were collected using a grid of 13 × 5 electrodes placed over the vastus medialis (VM). Intramuscular electrical stimulation was used to selectively activate two regions within VM. The distribution of EMG responses to stimulation was obtained by calculating the amplitude of the compound action potential for each channel; the position of the peak amplitude was tracked across knee angles to describe shifts of the active muscle regions under the electrodes. In a separate experiment, regional activation was investigated in 10 knee flexion-extension movements against a fixed resistance. Intramuscular stimulation of different VM regions resulted in clear differences in amplitude distribution along the columns of the electrode grid ( P < 0.001); changes in knee angle resulted in consistent shifts along the rows ( P < 0.01) and negligible shifts along the columns of the electrode grid. Regional VM activation was identified in dynamic movement, with distal shifts of the EMG distribution in the eccentric phase of the movement ( P < 0.05) and at more flexed knee angles ( P < 0.05). HDsEMG was used to describe regional activation across the VM that was not attributable to anatomic factors. Changes in muscle fiber orientation associated with knee joint angle mainly influence the amplitude distribution along the fiber direction. Future studies are needed to understand possible functional roles for regional activation within the VM in dynamic tasks.

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Lee, Jiseop, Dawon Park, Joo-Young Lee, and Jaebum Park. "Effect of Warm-Up Exercise on Functional Regulation of Motor Unit Activation during Isometric Torque Production." Journal of Human Kinetics 92 (April 25, 2024): 29–41. http://dx.doi.org/10.5114/jhk/185157.

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In this study, we tested several hypotheses related to changes in motor unit activation patterns after warm-up exercise. Fifteen healthy young men participated in the experiment and the main task was to produce voluntary torque through the elbow joint under the isometric condition. The experimental conditions consisted of two directions of torque, including flexion and extension, at two joint angles, 10° and 90°. Participants were asked to increase the joint torque to the maximal level at a rate of 10% of the maximum voluntary torque. The warm-up protocol followed the ACSM guidelines, which increased body temperature by approximately 1.5°C. Decomposition electromyography electrodes, capable of extracting multiple motor unit action potentials from surface signals, were placed on the biceps and triceps brachii muscles, and joint torque was measured on the dynamometer. The mean firing rate and the recruitment threshold of the decomposed motor units were quantified. In addition, a single motor unit activity from the spike train was quantified for each of five selected motor units. The magnitude of joint torque increased with the warm-up exercise for all the experimental conditions. The results of the motor unit analyses showed a positive and beneficial effect of the warm-up exercise, with an increase in both the mean firing rate and the recruitment threshold by about 56% and 33%, respectively, particularly in the agonist muscle. Power spectral density in the gamma band, which is thought to be the dominant voluntary activity, was also increased by the warm-up exercise only in the high threshold motor units.

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Akif Khidirov, Elgun Salahli, Akif Khidirov, Elgun Salahli. "PROGRAM FOR DETERMINING THE INFORMATIVE PARAMETERS OF SURFACE ELECTROMYOGRAPHIC SIGNALS." PIRETC-Proceeding of The International Research Education & Training Centre 27, no. 06 (August 25, 2023): 122–30. http://dx.doi.org/10.36962/piretc27062023-122.

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The article analyzes and calculates informative parameters of surface electromyographic signals (sEMS), which can be used to control biotechnical systems, as well as to diagnose the state of the musculoskeletal system. The analysis parameters in the time and frequency-time domains of the signal are considered. A program has been developed for calculating the informative indicators of the signal in the indicated areas. The program is implemented in the LabVIEW environment. To analyze the sEMG signal in the time domain, using the developed program, such indicators as Integral EMG, Average amplitude change, Wavelength, Simple quadratic integral, Absolute value of the 3rd time moment, and others were calculated; and to describe the signal spectrum by methods of time-frequency analysis, the average frequency of the spectrum (mean power frequency-MPF), the median frequency of the spectrum (median Frequency-MF), root mean square (RMS), power density spectrum (PDS), half width - the width of the spectrum at half maximum amplitude (HW). To test the program, files of real sEMQ signals were used. The calculated parameters of the sEMG analysis in the time and frequency-time domains make it possible to non-invasively and objectively assess the state of the musculoskeletal system. Keywords: Surface electromyographic signals, biotechnical systems, time-frequency analysis, Labvıew software.

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Lapatki, B. G., J. P. van Dijk, I. E. Jonas, M. J. Zwarts, and D. F. Stegeman. "A thin, flexible multielectrode grid for high-density surface EMG." Journal of Applied Physiology 96, no. 1 (January 2004): 327–36. http://dx.doi.org/10.1152/japplphysiol.00521.2003.

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Although the value of high-density surface electromyography (sEMG) has already been proven in fundamental research and for specific diagnostic questions, there is as yet no broad clinical application. This is partly due to limitations of construction principles and application techniques of conventional electrode array systems. We developed a thin, highly flexible, two-dimensional multielectrode sEMG grid, which is manufactured by using flexprint techniques. The material used as electrode carrier (Polyimid, 50 μm thick) allows grids to be cut out in any required shape or size. One universal grid version can therefore be used for many applications, thereby reducing costs. The reusable electrode grid is attached to the skin by using specially prepared double-sided adhesive tape, which allows the selective application of conductive cream only directly below the detection surfaces. To explore the practical possibilities, this technique was applied in single motor unit analysis of the facial musculature. The high mechanical flexibility allowed the electrode grid to follow the skin surface even in areas with very uneven contours, resulting in good electrical connections in the whole recording area. The silverchloride surfaces of the electrodes and their low electrode-to-skin impedances guaranteed high baseline stability and a low signal noise level. The electrode-to-skin attachment proved to withstand saliva and great tensile forces due to mimic contractions. The inexpensive, universally adaptable and minimally obstructive sensor allows the principal advantages of high-density sEMG to be extended to all skeletal muscles accessible from the skin surface and may lay the foundation for more broad clinical application of this noninvasive, two-dimensional sEMG technique.

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Steeg, Chiel van de, Andreas Daffertshofer, Dick F. Stegeman, and Tjeerd W. Boonstra. "High-density surface electromyography improves the identification of oscillatory synaptic inputs to motoneurons." Journal of Applied Physiology 116, no. 10 (May 15, 2014): 1263–71. http://dx.doi.org/10.1152/japplphysiol.01092.2013.

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Many studies have addressed corticomuscular coherence (CMC), but broad applications are limited by low coherence values and the variability across subjects and recordings. Here, we investigated how the use of high-density surface electromyography (HDsEMG) can improve the detection of CMC. Sixteen healthy subjects performed isometric contractions at six low-force levels using a pinch-grip, while HDsEMG of the adductor pollicis transversus and flexor and abductor pollicis brevis and whole-head magnetoencephalography were recorded. Different configurations were constructed from the HDsEMG grid, such as a bipolar and Laplacian montage, as well as a montage based on principal component analysis (PCA). CMC was estimated for each configuration, and the strength of coherence was compared across configurations. As expected, performance of the precision-grip task resulted in significant CMC in the β-frequency band (16–26 Hz). Compared with a bipolar EMG montage, all multichannel configurations obtained from the HDsEMG grid revealed a significant increase in CMC. The configuration, based on PCA, showed the largest (37%) increase. HDsEMG did not reduce the between-subject variability; rather, many configurations showed an increased coefficient of variation. Increased CMC presumably reflects the ability of HDsEMG to counteract inherent EMG signal factors—such as amplitude cancellation—which impact the detection of oscillatory inputs. In contrast, the between-subject variability of CMC most likely has a cortical origin.

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Guia Rosa, Igor Da, Marco Antonio Cavalcanti Garcia, and Marcio Nogueira De Souza. "Investigation of probability density functions in modeling sample distribution of surface electromyographic (sEMG) signals." Archives of Control Sciences 23, no. 4 (December 1, 2013): 381–93. http://dx.doi.org/10.2478/acsc-2013-0023.

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Abstract The surface electromyography signal (sEMG) has been typically modeled as a Gaussian random process. However, some authors have reported that the probability density functions (pdfs) associated with the sample distribution of sEMG signal exhibits a more peaked shape than one could expected for a Gaussian pdf. This work aimed to reinvestigate the profile of the sEMG pdfs during five different load levels of isometric contractions of biceps brachii muscle, and compared the adequacy of four different pdfs (Gaussian, Logistic, Cauchy, and Laplacian) in describing the sample distribution of such signal. Experimental pdfs were estimated for each subject and load condition. The comparison between experimental pdfs obtained from sEMG data of forty volunteers and four theoretical pdfs was performed by fitting these functions to its experimental counterpart, and using a mean absolute errors in the assessment of the best fit. On average, the Logistic pdf seemed to be the best one to describe the sample distribution of sEMG signal, although the probabilistic results, considering binomial trials, were significant for both Gaussian and Logistic pdfs.

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Hefferman, Gerald M., Fan Zhang, Michael J. Nunnery, and He Huang. "Integration of surface electromyographic sensors with the transfemoral amputee socket: A comparison of four differing configurations." Prosthetics and Orthotics International 39, no. 2 (January 27, 2014): 166–73. http://dx.doi.org/10.1177/0309364613516484.

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Background and aim: In recent years, there has been an increased interest in recording high-quality electromyographic signals from within the sockets of lower-limb amputees. However, successful recording presents major challenges to both researchers and clinicians. This article details and compares four prototypical integrated socket–sensor designs used to record electromyographic signals from within the sockets of transfemoral amputees. Technique: Four prototypical socket–sensor configurations were constructed and tested on a single transfemoral amputee asked to perform sitting/standing, stair ascent/descent, and level ground walking. The number of large-amplitude motion artifacts generated using each prototype was quantified, the amount of skin irritation documented, and the comfort level of each assembly subjectively assessed by the amputee subject. Discussion: Of the four configurations tested, the combination of a suction socket with integrated wireless surface electrodes generated the lowest number of large-amplitude motion artifacts, the least visible skin irritation, and was judged to be most comfortable by the amputee subject. Clinical relevance The collection of high-quality electromyographic signals from an amputee’s residual limb while maximizing patient comfort holds substantial potential to enhance neuromuscular clinical assessment and as a method of intuitive control of powered lower-limb prostheses.

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Krishnamani, Divya Bharathi, P. A. Karthick, and Ramakrishnan Swaminathan. "VARIATION OF INSTANTANEOUS SPECTRAL CENTROID ACROSS BANDS OF SURFACE ELECTROMYOGRAPHIC SIGNALS." Biomedical Sciences Instrumentation 57, no. 2 (April 1, 2021): 356–60. http://dx.doi.org/10.34107/yhpn9422.04356.

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Surface electromyography (sEMG) is a technique which noninvasively acquires the electrical activity of muscles and is widely used for muscle fatigue assessment. This study attempts to characterize the dynamic muscle fatiguing contractions with frequency bands of sEMG signals and a geometric feature namely the instantaneous spectral centroid (ISC). The sEMG signals are acquired from biceps brachii muscle of fifty-eight healthy volunteers. The frequency components of the signals are divided into low frequency band (10-45Hz), medium frequency band (55-95Hz) and high frequency band (95-400Hz). The signals associated with these bands are subjected to a Hilbert transform and analytical shape representation is obtained in the complex plane. The ISC feature is extracted from the resultant shape of the three frequency bands. The results show that this feature can differentiate the muscle nonfatigue and fatigue conditions (p<0.05). It is found the values of ISC is lower in fatigue conditions irrespective of frequency bands. It is also observed that the coefficient of variation of ISC in the low frequency band is less and it demonstrates the ability of handling inter-subject variations. Therefore, the proposed geometric feature from the low frequency band of sEMG signals could be considered for detecting muscle fatigue in various neuromuscular conditions.

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Sanger, Terence D. "Bayesian Filtering of Myoelectric Signals." Journal of Neurophysiology 97, no. 2 (February 2007): 1839–45. http://dx.doi.org/10.1152/jn.00936.2006.

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Surface electromyography is used in research, to estimate the activity of muscle, in prosthetic design, to provide a control signal, and in biofeedback, to provide subjects with a visual or auditory indication of muscle contraction. Unfortunately, successful applications are limited by the variability in the signal and the consequent poor quality of estimates. I propose to use a nonlinear recursive filter based on Bayesian estimation. The desired filtered signal is modeled as a combined diffusion and jump process and the measured electromyographic (EMG) signal is modeled as a random process with a density in the exponential family and rate given by the desired signal. The rate is estimated on-line by calculating the full conditional density given all past measurements from a single electrode. The Bayesian estimate gives the filtered signal that best describes the observed EMG signal. This estimate yields results with very low short-time variability but also with the capability of very rapid response to change. The estimate approximates isometric joint torque with lower error and higher signal-to-noise ratio than current linear methods. Use of the nonlinear filter significantly reduces noise compared with current algorithms, and it may therefore permit more effective use of the EMG signal for prosthetic control, biofeedback, and neurophysiology research.

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Chongzaijiao, He, D. S. V. Bandara, Hirofumi Nogami, and Jumpei Arata. "Prediction of finger motions based on high-density electromyographic signals using two-dimensional convolutional neural networks." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2023 (2023): 1A2—E06. http://dx.doi.org/10.1299/jsmermd.2023.1a2-e06.

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Redenbaugh, Margaret A., and Alan R. Reich. "Surface EMG and Related Measures in Normal and Vocally Hyperfunctional Speakers." Journal of Speech and Hearing Disorders 54, no. 1 (February 1989): 68–73. http://dx.doi.org/10.1044/jshd.5401.68.

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Surface electromyographic (EMG) signals were detected from the laryngeal area of 7 normal and 7 vocally hyperfunctional speakers during rest, two resisted-force maneuvers, vowel production, and connected speech. Vowel fundamental frequency, absolute and relative period perturbation, laryngeal-palpation ratings, and harshness ratings were acquired as well. The two groups differed significantly on all EMG measures except those associated with the resisted-force maneuvers, the vowel EMG-to-rest EMG ratio, and the speech EMG-to-rest EMG ratio. Moderately high correlations were evident between selected clinical measures and speech EMG values.

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Sproll, Tobias, and Anton Schiela. "An adjoint approach to identification in electromyography: modeling and first order optimality conditions." Inverse Problems 37, no. 12 (November 26, 2021): 125012. http://dx.doi.org/10.1088/1361-6420/ac362c.

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Abstract In medical treatment it can be necessary to know the position of a motor unit in a muscle. Recent advances in high-density surface electromyography (EMG) measurement have opened the possibility of extracting information about single motor units. We present a mathematical approach to identify these motor units. On the base of an electrostatic forward model, we introduce an adjoint approach to efficiently simulate a surface EMG measurement and an optimal control approach to identify these motor units. We show basic results on existence of solutions and first-order optimality conditions.

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McHugh, Malachy P., Timothy F. Tyler, Michael G. Browne, Gilbert W. Gleim, and Stephen J. Nicholas. "Electromyographic Predictors of Residual Quadriceps Muscle Weakness after Anterior Cruciate Ligament Reconstruction." American Journal of Sports Medicine 30, no. 3 (May 2002): 334–39. http://dx.doi.org/10.1177/03635465020300030601.

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Background Despite the high prevalence of residual quadriceps muscle weakness after anterior cruciate ligament reconstruction, specific predictive factors have not been identified. Hypothesis Electromyographic analysis is a better predictor of residual muscle weakness than is preoperative strength. Study Design Prospective cohort study. Methods The quadriceps muscle strength of 37 patients (25 men, 12 women) was measured before reconstruction and 5 weeks and 6 months after surgery. Quadriceps surface electromyographic signals were recorded during all of the strength tests. Integrated electromyographic analysis and median frequency measurements were computed as deficits on the involved side. Patients also performed a single-legged hop test at the 6-month follow-up examination. Results The patients had significantly lower strength, integrated electromyographic analysis, and median frequency measurements on the involved side at all three time intervals. The best predictor of the quadriceps muscle strength deficit at 6 months was the combination of the preoperative median frequency deficit and the 5-week postoperative strength deficit. The best predictor of the hop test deficit at 6 months was the combination of preoperative deficits in integrated electromyographic analysis and median frequency. Conclusion Preoperative electromyographic indices of quadriceps muscle function and early postoperative strength were predictive of residual weakness and impaired function 6 months after reconstruction.

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Lin, Tzu-En, Chih-Ning Tsai, Pei-Wen Yang, and Chih-Ching Huang. "(Invited) Air-Permeable MXene Electrode with Miura-ori Structure for Biosensing." ECS Transactions 111, no. 3 (May 19, 2023): 49–54. http://dx.doi.org/10.1149/11103.0049ecst.

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In this work, we present an air-permeable MXene electrode capable of recording surface electromyographic (sEMG) signals on the skin surface based on the Miura-ori structure. MXene is a two-dimensional (2D) nanomaterial composed of transition metal carbides, nitrides, and carbonitrides developed in recent years. Taking advantage of the Miura-ori structure, MXene-based electrodes have high breathability as well as low and stable electrode-skin interfacial impedances, facilitating long-term reliable electrophysiological monitoring. The electrolytic gel on conventional wet Ag/AgCl gel electrodes increases the impedance between the electrode and the skin as it gradually dries, inhibits sweat evaporation and affects signal acquisition. Therefore, we provide a fascinating electrode design that can be used to obtain high-quality sEMG signals for assessing body movements such as swallowing.

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Stock, Matt S., and Brennan J. Thompson. "Motor Unit Interpulse Intervals During High Force Contractions." Motor Control 20, no. 1 (January 2016): 70–86. http://dx.doi.org/10.1123/mc.2014-0089.

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We examined the means, medians, and variability for motor-unit interpulse intervals (IPIs) during voluntary, high force contractions. Eight men (mean age = 22 years) attempted to perform isometric contractions at 90% of their maximal voluntary contraction force while bipolar surface electromyographic (EMG) signals were detected from the vastus lateralis and vastus medialis muscles. Surface EMG signal decomposition was used to determine the recruitment thresholds and IPIs of motor units that demonstrated accuracy levels ≥ 96.0%. Motor units with high recruitment thresholds demonstrated longer mean IPIs, but the coefficients of variation were similar across all recruitment thresholds. Polynomial regression analyses indicated that for both muscles, the relationship between the means and standard deviations of the IPIs was linear. The majority of IPI histograms were positively skewed. Although low-threshold motor units were associated with shorter IPIs, the variability among motor units with differing recruitment thresholds was comparable.

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Luu, Gia Thien, Abdelbassit Boualem, Tran Trung Duy, Philippe Ravier, and Olivier Butteli. "Time-Varying Delay Estimation Applied to the Surface Electromyography Signals Using the Parametric Approach." Fluctuation and Noise Letters 17, no. 02 (May 2, 2018): 1850015. http://dx.doi.org/10.1142/s0219477518500153.

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Muscle Fiber Conduction Velocity (MFCV) can be calculated from the time delay between the surface electromyographic (sEMG) signals recorded by electrodes aligned with the fiber direction. In order to take into account the non-stationarity during the dynamic contraction (the most daily life situation) of the data, the developed methods have to consider that the MFCV changes over time, which induces time-varying delays and the data is non-stationary (change of Power Spectral Density (PSD)). In this paper, the problem of TVD estimation is considered using a parametric method. First, the polynomial model of TVD has been proposed. Then, the TVD model parameters are estimated by using a maximum likelihood estimation (MLE) strategy solved by a deterministic optimization technique (Newton) and stochastic optimization technique, called simulated annealing (SA). The performance of the two techniques is also compared. We also derive two appropriate Cramer–Rao Lower Bounds (CRLB) for the estimated TVD model parameters and for the TVD waveforms. Monte-Carlo simulation results show that the estimation of both the model parameters and the TVD function is unbiased and that the variance obtained is close to the derived CRBs. A comparison with non-parametric approaches of the TVD estimation is also presented and shows the superiority of the method proposed.

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De Luca, Carlo J., Shey-Sheen Chang, Serge H. Roy, Joshua C. Kline, and S. Hamid Nawab. "Decomposition of surface EMG signals from cyclic dynamic contractions." Journal of Neurophysiology 113, no. 6 (March 15, 2015): 1941–51. http://dx.doi.org/10.1152/jn.00555.2014.

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Over the past 3 decades, various algorithms used to decompose the electromyographic (EMG) signal into its constituent motor unit action potentials (MUAPs) have been reported. All are limited to decomposing EMG signals from isometric contraction. In this report, we describe a successful approach to decomposing the surface EMG (sEMG) signal collected from cyclic (repeated concentric and eccentric) dynamic contractions during flexion/extension of the elbow and during gait. The increased signal complexity introduced by the changing shapes of the MUAPs due to relative movement of the electrodes and the lengthening/shortening of muscle fibers was managed by an incremental approach to enhancing our established algorithm for decomposing sEMG signals obtained from isometric contractions. We used machine-learning algorithms and time-varying MUAP shape discrimination to decompose the sEMG signal from an increasingly challenging sequence of pseudostatic and dynamic contractions. The accuracy of the decomposition results was assessed by two verification methods that have been independently evaluated. The firing instances of the motor units had an accuracy of ∼90% with a MUAP train yield as high as 25. Preliminary observations from the performance of motor units during cyclic contractions indicate that during repetitive dynamic contractions, the control of motor units is governed by the same rules as those evidenced during isometric contractions. Modifications in the control properties of motoneuron firings reported by previous studies were not confirmed. Instead, our data demonstrate that the common drive and hierarchical recruitment of motor units are preserved during concentric and eccentric contractions.

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Yang, Kerong, Senhao Zhang, Xuhui Hu, Jiuqiang Li, Yingying Zhang, Yao Tong, Hongbo Yang, and Kai Guo. "Stretchable, Flexible, Breathable, Self-Adhesive Epidermal Hand sEMG Sensor System." Bioengineering 11, no. 2 (February 1, 2024): 146. http://dx.doi.org/10.3390/bioengineering11020146.

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Hand function rehabilitation training typically requires monitoring the activation status of muscles directly related to hand function. However, due to factors such as the small surface area for hand-back electrode placement and significant skin deformation, the continuous real-time monitoring of high-quality surface electromyographic (sEMG) signals on the hand-back skin still poses significant challenges. We report a stretchable, flexible, breathable, and self-adhesive epidermal sEMG sensor system. The optimized serpentine structure exhibits a sufficient stretchability and filling ratio, enabling the high-quality monitoring of signals. The carving design minimizes the distribution of connecting wires, providing more space for electrode reservation. The low-cost fabrication design, combined with the cauterization design, facilitates large-scale production. Integrated with customized wireless data acquisition hardware, it demonstrates the real-time multi-channel sEMG monitoring capability for muscle activation during hand function rehabilitation actions. The sensor provides a new tool for monitoring hand function rehabilitation treatments, assessing rehabilitation outcomes, and researching areas such as prosthetic control.

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Chen, Maoqi, Ales Holobar, Xu Zhang, and Ping Zhou. "Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition." Neural Plasticity 2016 (2016): 1–5. http://dx.doi.org/10.1155/2016/3489540.

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Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average,10.6±4.3common motor units were identified from each trial, which showed a very high matching rate of97.85±1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield.

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Del Vecchio, A., A. Holobar, D. Falla, F. Felici, R. M. Enoka, and D. Farina. "Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals." Journal of Electromyography and Kinesiology 53 (August 2020): 102426. http://dx.doi.org/10.1016/j.jelekin.2020.102426.

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Sandoval-Rodriguez, C. L., A. C. Pita-Mejia, R. Villamizar-Mejia, B. E. Tarazona-Romero, and Omar Lengerke-Perez. "Model to Relationship the Speed of Hand Movements with the SEMG Signals from the Forearm." Journal of Physics: Conference Series 2224, no. 1 (April 1, 2022): 012094. http://dx.doi.org/10.1088/1742-6596/2224/1/012094.

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Abstract Various previous works have sought to achieve hand prostheses with natural movements. It has been employed tools to recognize patterns of surface electromyographic signals associated with each move. Although many successful studies classify some types of hand movements with high performance, the results show that the speed and strength must be analyzed so that the resulting moves are like those of a natural hand. This study evaluates 23 healthy subjects at two different speeds and six types of movements (pronation, supination, ulnar deviation, radial deviation, flexion, and extension -276 records of SEMG and Velocity). The objective was to obtain a model (transfer function) that would allow the relation of the velocity profiles with the tone of the forearm SEMG signals. The results show models with an average RMSE of 18.55% for slow movements using low-order systems (2). The parameters of the models between subjects are very different, with high coefficients of variation and standard deviations, which implies that the fitting must be for each subject.

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St. George, L., T. J. P. Spoormakers, S. H. Roy, S. J. Hobbs, H. M. Clayton, J. Richards, and F. M. Serra Bragança. "Reliability of surface electromyographic (sEMG) measures of equine axial and appendicular muscles during overground trot." PLOS ONE 18, no. 7 (July 14, 2023): e0288664. http://dx.doi.org/10.1371/journal.pone.0288664.

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The reliability of surface electromyography (sEMG) has not been adequately demonstrated in the equine literature and is an essential consideration as a methodology for application in clinical gait analysis. This observational study investigated within-session, intra-subject (stride-to-stride) and inter-subject reliability, and between-session reliability of normalised sEMG activity profiles, from triceps brachii (triceps), latissimus dorsi (latissimus), longissimus dorsi (longissimus), biceps femoris (biceps), superficial gluteal (gluteal) and semitendinosus muscles in n = 8 clinically non-lame horses during in-hand trot. sEMG sensors were bilaterally located on muscles to collect data during two test sessions (session 1 and 2) with a minimum 24-hour interval. Raw sEMG signals from ten trot strides per horse and session were DC-offset removed, high-pass filtered (40 Hz), full-wave rectified, and low-pass filtered (25 Hz). Signals were normalised to peak amplitude and percent stride before calculating intra- and inter-subject ensemble average sEMG profiles across strides for each muscle and session. sEMG profiles were assessed using waveform similarity statistics: the coefficient of variation (CV) to assess intra- and inter-subject reliability and the adjusted coefficient of multiple correlation (CMC) to evaluate between-session reliability. Across muscles, CV data revealed that intra-horse sEMG profiles within- and between-sessions were comparatively more reliable than inter-horse profiles. Bilateral gluteal, semitendinosus, triceps and longissimus (at T14 and L1) and right biceps showed excellent between-session reliability with group-averaged CMCs > 0.90 (range 0.90–0.97). Bilateral latissimus and left biceps showed good between-session reliability with group-averaged CMCs > 0.75 (range 0.78–0.88). sEMG profiles can reliably describe fundamental muscle activity patterns for selected equine muscles within a test session for individual horses (intra-subject). However, these profiles are more variable across horses (inter-subject) and between sessions (between-session reliability), suggesting that it is reasonable to use sEMG to objectively monitor the intra-individual activity of these muscles across multiple gait evaluation sessions at in-hand trot.

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Ito, Masateru, Fumio Nakamura, Akira Baba, Kaoru Tamada, Hirobumi Ushijima, King Hang Aaron Lau, Abhijit Manna, and Wolfgang Knoll. "Enhancement of Surface Plasmon Resonance Signals by Gold Nanoparticles on High-Density DNA Microarrays." Journal of Physical Chemistry C 111, no. 31 (August 2007): 11653–62. http://dx.doi.org/10.1021/jp070524m.

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Carriou, Vincent, Sofiane Boudaoud, Jeremy Laforet, and Fouaz Sofiane Ayachi. "Fast generation model of high density surface EMG signals in a cylindrical conductor volume." Computers in Biology and Medicine 74 (July 2016): 54–68. http://dx.doi.org/10.1016/j.compbiomed.2016.04.019.

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Hajian, Gelareh, Ali Etemad, and Evelyn Morin. "Automated Channel Selection in High-Density sEMG for Improved Force Estimation." Sensors 20, no. 17 (August 27, 2020): 4858. http://dx.doi.org/10.3390/s20174858.

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Accurate and real-time estimation of force from surface electromyogram (EMG) signals enables a variety of applications. We developed and validated new approaches for selecting subsets of high-density (HD) EMG channels for improved and lower-dimensionality force estimation. First, a large dataset was recorded from a number of participants performing isometric contractions in different postures, while simultaneously recording HD-EMG channels and ground-truth force. The EMG signals were acquired from three linear surface electrode arrays, each with eight monopolar channels, and were placed on the long head and short head of the biceps brachii and brachioradialis. After data collection and pre-processing, fast orthogonal search (FOS) was employed for force estimation. To select a subset of channels, principal component analysis (PCA) in the frequency domain and a novel index called the power-correlation ratio (PCR), which maximizes the spectral power while minimizing similarity to other channels, were used. These approaches were compared to channel selection using time-domain PCA. We selected one, two, and three channels per muscle from the original seven differential channels to reduce the redundancy and correlation in the dataset. In the best case, we achieved an approximate improvement of 30% for force estimation while reducing the dimensionality by 57% for a subset of three channels.

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Pietraszewski, Przemysław, Artur Gołaś, Michał Krzysztofik, Marta Śrutwa, and Adam Zając. "Evaluation of Lower Limb Muscle Electromyographic Activity during 400 m Indoor Sprinting among Elite Female Athletes: A Cross-Sectional Study." International Journal of Environmental Research and Public Health 18, no. 24 (December 14, 2021): 13177. http://dx.doi.org/10.3390/ijerph182413177.

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The purpose of this cross-sectional study was to analyze changes in normalized surface electromyography (sEMG) signals for the gastrocnemius medialis, biceps femoris, gluteus maximus, tibialis anterior, and vastus lateralis muscles occurring during a 400 m indoor sprint between subsequent curved sections of the track. Ten well-trained female sprinters (age: 21 ± 4 years; body mass: 47 ± 5 kg; body height: 161 ± 7 cm; 400 m personal best: 52.4 ± 1.1 s) performed an all-out 400 m indoor sprint. Normalized sEMG signals were recorded bilaterally from the selected lower limb muscles. The two-way ANOVA (curve × side) revealed no statistically significant interaction. However, the main effect analysis showed that normalized sEMG signals significantly increased in subsequent curves run for all the studied muscles: gastrocnemius medialis (p = 0.003), biceps femoris (p < 0.0001), gluteus maximus (p = 0.044), tibialis anterior (p = 0.001), and vastus lateralis (p = 0.023), but differences between limbs were significant only for the gastrocnemius medialis (p = 0.012). The results suggest that the normalized sEMG signals for the lower limb muscles increased in successive curves during the 400 m indoor sprint. Moreover, the gastrocnemius medialis of the inner leg is highly activated while running curves; therefore, it should be properly prepared for high demands, and attention should be paid to the possibility of the occurrence of a negative adaptation, such as asymmetries.

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Lin, Tzu-En, Chih-Ning Tsai, Pei-Wen Yang, and Chih-Ching Huang. "(Invited) Air-Permeable MXene Electrode with Miura-ori Structure for Biosensing." ECS Meeting Abstracts MA2023-01, no. 34 (August 28, 2023): 1938. http://dx.doi.org/10.1149/ma2023-01341938mtgabs.

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MXene is a two-dimensional nanomaterial composed of transition metal carbides/nitrides/carbonitrides developed in recent years. The general formula of MXene is Mn+1XnTx, where X is C or N, M is a transition metal, n is between 1 and 3, and Tx represents different functional groups on the surface. Currently, a popular method for preparing MXene is MAX phase selective etching of A-layer atoms. It has often been used as an useful materials for sensors or as biosensors due to its outstanding physical-mechanical properties, excellent electrical conductivity, and nanostructure to improve the sensitivity, conductivity, and catalytic performance of the sensing devices. In this work, we present an air-permeable MXene electrode capable of recording electromyographic (EMG) signals on the skin surface based on Miura-ori structure. Taking advantages of the Miura-ori structure, MXene-based electrodes have high breathability and low and stable electrode-skin interfacial impedances, facilitating long-term reliable electrophysiological monitoring. The electrolytic gel on top of the conventional wet Ag/AgCl gel electrodes increases the impedance between the electrode and the skin as it gradually dries, inhibiting sweat evaporation and affecting signal acquisition. Therefore, we provide a fascinating electrode design that can be used to obtain high-quality sEMG signals for evaluating body movements such as swallowing.

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Journal articles on the topic 'High density surface electromyographic signals'

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