Literatura académica sobre el tema "High density surface electromyographic signals"
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Artículos de revistas sobre el tema "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 (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 (2020): 3501–9. http://dx.doi.org/10.1109/tbme.2020.2989311.
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Song, Rui, Xu Zhang, Xi Chen, et al. "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 (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, et al. "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 (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 (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 (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 (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.
Tesis sobre el tema "High density surface electromyographic signals"
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Imrani, Sallak Loubna. "Evaluation of muscle aging using high density surface electromyography." Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2647.
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Avec le vieillissement de la population, préserver la fonction musculaire est important pour éviter la perte de mobilité et d'autonomie. De nos jours, la prévention de la maladie musculaire, la sarcopénie, est une préoccupation majeure et des facteurs de risque importants tels que l'âge avancé ainsi que des facteurs modifiables, notamment une faible activité physique et une alimentation déséquilibrée ont été identifiés. Compte tenu de la croissance des populations plus âgées et de la diminution de l'activité physique, qui touche également les jeunes citoyens, la sensibilisation à la qualité musculaire peut être cruciale pour promouvoir un vieillissement en bonne santé dans nos sociétés. Les besoins en évaluations fonctionnelles musculaires ont été exprimés par les chercheurs et les cliniciens. Le groupe de travail européen sur la sarcopénie chez les personnes âgées (EWGSOP) recommande de définir la sarcopénie comme la présence à la fois d'une faible masse musculaire et d'une faible fonction musculaire (force et performance physique). Pour cela, nous avons développé une méthode d’évaluation du vieillissement musculaire, en utilisant une technologie ambulatoire et non invasive, appelée technologie d'électromyographie de surface haute densité (HD-sEMG), à travers un projet de recherche clinique sur cinq catégories d'âge (25 à 74 ans), actifs et sédentaires. Nous avons réalisé une étude comparative avec une analyse complète et multimodale du rectus femoris (RF), muscle impliqué dans les mouvements de la vie quotidienne, pour dévoiler le potentiel prometteur de la technique HD sEMG, par rapport aux techniques cliniques classiques, l’objectif étant de détecter les changements précoces de la qualité de la fonction musculaire impactée par le vieillissement et le niveau d'activité physique. La partie clinique de ce projet de thèse a été financée par une subvention européenne, EIT Health. En analysant principalement la dynamique de contraction musculaire et l'intensité du rectus femoris, nos résultats ont montré que la technique HD-sEMG, était capable de discriminer entre les cinq catégories d'âge de sujets sains physiquement actifs. Plus intéressant encore, les scores HD-sEMG proposés discriminaient entre les participants actifs et sédentaires, de la même catégorie d'âge (45-54 ans), contrairement aux paramètres cliniques et aux autres techniques couramment utilisées (absortiométrie biphotonique par rayons X, DXA et échographie). De plus, ces scores pour les participants sédentaires de cette catégorie d'âge étaient significativement plus proches de ceux des participants actifs des catégories d'âge supérieures (55-64 ans et 65-74 ans). Cela suggère fortement qu'un mode de vie sédentaire semble accélérer le processus de vieillissement musculaire au niveau anatomique et fonctionnel, et ce processus accéléré subtil peut être détecté par la technique HD-sEMG. Ces résultats préliminaires prometteurs pourraient contribuer au développement d’un outil intéressant aux cliniciens pour améliorer à la fois la précision et la sensibilité de l'évaluation musculaire utile pour les programmes de prévention et de réadaptation afin d'éviter ou de retarder la sarcopénie, problème de santé publique actuel alerté par l'Organisation Mondiale de la Santé (OMS) et promouvoir un vieillissement en bonne santé<br>With the aging of the population, preserving muscle function is important to prevent loss of mobility and autonomy. Nowadays, the prevention of the muscle disease, sarcopenia, is a major concern and important risk factors such as older age as well as modifiable factors including low physical activity and unhealthy diet have been identified. Considering the growth of older populations and the decreased physical activity, which also includes young citizens, muscle quality awareness can be crucial in promoting a healthy aging process in our societies. Muscle functional assessments needs were expressed by researchers and clinicians, The European Working Group on Sarcopenia in Older People (EWGSOP) recommends defining sarcopenia as the presence of both low muscle mass and low muscle function (strength, and physical performance). For this purpose, we have developed a method for muscle aging evaluation, using an ambulatory and non-invasive technology, called high-density surface electromyography (HDsEMG), through a clinical research project on five age categories (25 to 74 yrs.). We performed a comparative study with a complete and multimodal analysis of the rectus femoris, muscle involved in daily life motions, in order to reveal the promising potential of the HD-sEMG technique, compared to conventional clinical techniques, to detect early changes in the quality of muscle function impacted by aging and physical activity level. The clinical part of this thesis project was funded by a European grant, EITH Health. By analyzing both muscle contraction dynamics and intensity of the rectus femoris, our results showed that the HD-sEMG technique, was able to discriminate between the five age categories of healthy physically active subjects. More interestingly, the proposed HD-sEMG scores discriminated between active and sedentary participants, from the same age category(45-54 yrs.), in contrary to clinical parameters and others usual techniques (dual-energy x-ray absorptiometry, DXA and ultrasonography). In addition, these scores for sedentary participants from this age category were significantly closer to those of active participants from higher age categories (55-64 yrs. and 65-74 yrs.). This strongly suggests that sedentary lifestyle seems to accelerate the muscle aging process at both anatomical and functional level, and this subtle accelerated process can be detected by the HD-sEMG technique. These promising preliminary results can contribute to the development of an interesting tool for clinicians to improve both accuracy and sensitivity of functional muscle evaluation useful for prevention and rehabilitation to avoid the effects of unhealthy lifestyle that can potentially lead to sarcopenia. This can support also the actual public health concern alerted by Word Health Organization (WHO) regarding aging and sarcopenia, to promote healthy aging
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Magbonde, Abilé. "Séparation de signaux électromyographiques de surface à haute densité pour la réduction de la diaphonie." Electronic Thesis or Diss., Université Grenoble Alpes, 2024. http://www.theses.fr/2024GRALT008.
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L’utilisation du signal électrique musculaire de surface (EMG) dans une perspective biomécanique, thérapeutique ou pour la commande nécessite une forte sélectivité spatiale des signaux. Pour des muscles contigus, cette contrainte est rarement observée rendant l’utilisation du signal EMG difficile. La diaphonie, ou contamination croisée des signaux, inhérentes aux enregistrements doit alors être supprimée.Cette thèse a pour but de proposer des méthodes pour séparer la diaphonie lorsque les muscles extenseurs de l'index et du petit doigt sont en contraction simultanée. Notre travail consiste alors à extraire l’activité musculaire liée à chaque muscle dans un contexte de séparation de sources. Pour cela, une première partie du travail a consisté à élaborer une base de données, de qualité et exploitable, en enregistrant de manière non invasive les signaux EMG à partir de matrices d’électrodes, et à la mettre en forme pour la mettre à disposition de la communauté scientifique. Dans un second temps, diverses approches de traitement du signal ont été mise en œuvre pour réduire la diaphonie. Au final, nous proposons une méthode basée sur la décomposition tensorielle non négative de type PARAFAC2 appliquée aux enveloppes des signaux EMG obtenues à partir de la RMS sur des fenêtres glissantes afin de séparer l’activité de chaque muscle. L’originalité du modèle proposé repose sur l’ajout de deux contraintes principales en plus de celles relatives à PARAFAC2. La première contrainte est liée à la physiologie musculaire et implique la continuité spatiale des cartes d’acquisition, tandis que la seconde contrainte est relative à notre protocole expérimental et introduit de la parcimonie. Le modèle a été testé et validé sur des signaux réels puis sur des mélanges artificiels de signaux réels. La méthode proposée offre de meilleures performances de séparation par rapport à l’algorithme NN-PARAFAC2 et plus généralement par rapport à l’ensemble des autres méthodes de séparation de sources classiquement utilisées. Les limites et perspectives sont envisagées dans la dernière partie du document<br>The use of surface electromyographic (EMG) signals in a biomechanical, therapeutic, or control perspective requires a high spatial selectivity of the signals. In the case of adjacent muscles, this constraint is rarely met, making EMG signal utilization challenging. Crosstalk, or signal contamination inherent in recordings, must be eliminated.This thesis aims to propose methods for separating crosstalk when the extensor muscles of the index and little finger contract simultaneously. Our work focuses on extracting the muscle activity associated with each muscle in a source separation context. To achieve this, the initial part of the work involved creating a high-quality and usable database by non-invasively recording EMG signals from electrode arrays and formatting it for the scientific community's use. In the next phase, various signal processing approaches were employed to reduce crosstalk. Ultimately, we present a method based on non-negative tensor decomposition of the PARAFAC2 type applied to the envelopes of EMG signals obtained through root mean square (RMS) on sliding windows to separate the activity of each muscle. The uniqueness of the proposed model lies in the addition of two primary constraints in addition to those associated with PARAFAC2. The first constraint is related to muscle physiology and involves spatial continuity in the acquisition maps, while the second constraint is specific to our experimental protocol and introduces sparsity.The model was tested and validated on real signals and artificial mixtures of real signals. The proposed method demonstrates superior separation performance compared to the NN-PARAFAC2 algorithm and, more broadly, relative to conventional source separation methods. The document concludes by discussing its limitations and potential future directions
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Berro, Soumaya. "Identification of muscle activation schemes by inverse methods applied on HD-sEMG signals." Electronic Thesis or Diss., Compiègne, 2022. http://www.theses.fr/2022COMP2708.
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L'identification rapide ou en temps réel de l'activation spatio-temporelle des unités motrices (UM) qui représentent les unités fonctionnelles du système neuromusculaire est fondamentale dans les applications de contrôle des prothèses et en réhabilitation fonctionnelle. Cependant, cette procédure demande un temps de calcul énorme. Par conséquent, le travail de cette thèse a été consacré à fournir un algorithme permettant l'identification en temps réel des stratégies d'activation spatiale et temporelle des UMs en appliquant des méthodes inverses sur les signaux HD-sEMG (électromyogramme de surface à haute densité) à partir d'une grille placée sur le Biceps Brachial (BB). À cette fin, nous proposons une approche innovante, qui implique l'utilisation de la méthode inverse classique de minimisation de norme et une interpolation de courbe en 3D, à savoir l'approche est nommée CFB-MNE. Cette méthode, fondée sur l'identification inverse (estimation de la norme minimale) couplée à un dictionnaire des potentiels d'action des unités motrices simulées (MUAP) d'un modèle récent et testée sur des simulations, a permis la localisation en temps réel des unités motrices individuelles simulées. Une analyse de robustesse (modifications anatomiques, physiologiques et instrumentales) a ensuite été effectuée pour vérifier l'efficacité de l'algorithme proposé. Enfin, l'algorithme proposé a été testé sur des UMs avec des schémas de recrutement réalistes donnant des résultats prometteurs et encourageants en identification spatiale et temporelle sur trois scenarios. Pour conclure, en perspectives, les résultats prometteurs obtenus suggèrent l'utilisation de l'apprentissage automatique et de l'intelligence artificielle (IA) pour améliorer encore les performances de l'algorithme proposé<br>Fast or real-time identification of the spatiotemporal activation of Motor Units (MUs), functional units of the neuromuscular system, is fundamental in applications as prosthetic control and rehabilitation guidance but often dictates expensive computational times. Therefore, the thesis work was devoted to providing an algorithm that enables the real-time identification of MU spatial and temporal activation strategies by applying inverse methods on HD-sEMG (high-density surface electromyogram) signals from a grid placed over the Biceps Brachii (BB). For this purpose, we propose an innovative approach, that involves the use of the classical minimum norm inverse method and a 3D fitting curve interpolation, namely CFB-MNE approach. This method, based on inverse identification (minimum norm estimation) coupled to simulated motor unit action potential (MUAP) dictionary from a recent model and tested on simulations, allowed the real time localization of simulated individual motor units. A robustness analysis (anatomical, physiological, and instrumental modifications) was then performed to verify the efficiency of the proposed algorithm. Finally, the proposed algorithm was tested on MUs with realistic recruitment patterns giving promising results in both spatial and temporal identification. To conclude, a door to future perspectives was opened, according to the obtained promising results, suggesting the use of machine learning and artificial intelligence (AI) to further boost the performance of the proposed algorithm
Capítulos de libros sobre el tema "High density surface electromyographic signals"
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Oliveira, I. S., M. A. Favretto, S. Cossul, and J. L. B. Marques. "Development of a Matlab-Based Graphical User Interface for Analysis of High-Density Surface Electromyography Signals." In XXVII Brazilian Congress on Biomedical Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-70601-2_267.
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Okada, Yoshio. "Physiological Bases of Magnetoencephalography and Electroencephalography." In Fifty Years of Magnetoencephalography. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190935689.003.0004.
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Understanding the physiological bases of magnetoencephalography (MEG) and electroencephalography (EEG) provides the foundation for developing these techniques as tools for studying human brain functions because this information can serve as a guide for planning experimental studies and for interpreting the data. During the past 50 years, the concept of electrophysiology of neurons has been profoundly modified as new types of active conductance have been discovered in the dendrites and soma. The biophysical models of individual neurons and neuronal networks developed within the framework of modern electrophysiology have provided quantitatively accurate accounts of evoked magnetic fields, extracellular potentials, and intracellular potentials in principal neurons in the tissues within a single theoretical framework. These results are consistent with the conclusion that intracellular currents in active tissues produce both MEG and EEG signals in the cerebellum, hippocampus, and cerebral cortex. We now know that the calcium and potassium currents are the major currents shaping the waveforms of MEG and EEG and that the sodium and potassium currents generate the spikes and high-frequency signals detectable outside the brain. The current dipole moment density, defined as current dipole moment per unit surface area of the active cortex, is governed by the intracellular volume fraction and basic kinetics of the active conductances. This quantity, which is conserved across the evolutionary scale ranging from reptiles to humans, may serve as a useful physiological constraint in interpreting MEG and EEG signals. It is hoped that this foundation will help advance the research on human brain functions.
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Boudriki Semlali, Badr-Eddine, Carlos Molina, Mireia Carvajal Librado, Hyuk Park, and Adriano Camps. "Potential Earthquake Proxies from Remote Sensing Data." In New Insights on Disaster Risk Reduction [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1005382.
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At present, there is no clear scientific evidence of reliable earthquake precursors that can be used as an early warning system. However, many studies have also reported the existence of faint signatures that appear to be coupled to the occurrence of earthquakes. These anomalies have traditionally been detected using data from in-situ sensors near high-seismicity regions. On the other hand, remote sensors offer the potential of large spatial coverage and frequent revisit time, allowing the observation of remote areas such as deserts, mountains, polar caps, or the ocean. This chapter revises the state-of-the-art of the understanding of lithosphere–atmosphere–ionosphere coupling. It also presents recent studies by the authors’ ongoing investigation on short-to-midterm earthquake precursors. The Earth observation variables discussed are (1) surface temperature anomalies from thermal infrared or microwave radiometer measurements, (2) atmospheric signatures, (3) ionospheric total electron density fluctuations or scintillation measured from GNSS signals, and (4) other geophysical variables, including geomagnetic field fluctuations, changes in the Schumann resonance frequency, or low-frequency electromagnetic radiation. However, despite the seismic hazard risk models that exist and the results shown by these studies, it is still very difficult to predict the occurrence of earthquakes.
Actas de conferencias sobre el tema "High density surface electromyographic signals"
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Marateb, H. R., M. Rojas-Martinez, M. A. Mananas Villanueva, and R. Merletti. "Robust outlier detection in high-density surface electromyographic signals." In 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iembs.2010.5627280.
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Ilg, Julian, Lukas Hinderer, Konstantin Struebig, and Tim C. Lueth. "A Sensor-Integrated Textile for the Acquisition of Upper Extremity Electromyographic Signals." In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-112239.
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Abstract This paper presents a novel sensor-integrated wearable textile for the acquisition of upper extremity (UE) electromyographic (EMG) signals. The device utilizes dry high-density electrodes that are non-invasive, comfortable to wear, and do not require exact positioning over the respective muscles due to the high number and density of electrodes. The wearable EMG-textile was designed for ease of use and can be easily donned and doffed by the user. The authors tested the device on a group of 10 participants to recognize hand gestures via the acquired EMG signals. To enable gesture recognition, the authors compared various deep learning models and conventional classifiers, observing that a convolutional neural network (CNN) trained on Willison Amplitude (WAMP) features produced the most promising results. The trained CNN achieved an accuracy of 82.7% in recognizing 14 different hand gestures. Overall, the results of this study suggest that the proposed sensor-integrated wearable textile has the potential to be a convenient and effective tool for the acquisition and analysis of EMG signals. Further studies are needed to evaluate the effectiveness of the device in real-world scenarios and to investigate its potential for use in other applications.
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Montazerin, Mansooreh, Soheil Zabihi, Elahe Rahimian, Arash Mohammadi, and Farnoosh Naderkhani. "ViT-HGR: Vision Transformer-based Hand Gesture Recognition from High Density Surface EMG Signals." In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2022. http://dx.doi.org/10.1109/embc48229.2022.9871489.
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Vo-Dinh, T., and D. L. Stokes. "SERODS: A New Principle for High-Density Optical Data Storage." In Optical Data Storage. Optica Publishing Group, 1994. http://dx.doi.org/10.1364/ods.1994.tud1.
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SERODS is a new technology for high-density optical disk storage based on the surface-enhanced Raman effect.(1) The SERODS technology is based on the principle that the enhanced light-emitting properties of certain molecules embedded in an optical medium can be altered at the molecular level to store information. When they are close to a rough metal surface, certain molecules emit a strongly enhanced light called surface-enhance Raman light which is characteristic of their vibrations. Normal Raman signals are generally very weak and cannot be easily detected. The enhanced emission is due to the Surface-Enhanced Raman Scattering (SERS) effect, which can enhance the Raman signal up to 108 times.
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Gibson, Alison E., Mark R. Ison, and Panagiotis Artemiadis. "User-Independent Hand Motion Classification With Electromyography." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3832.
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Electromyographic (EMG) processing is an important research area with direct applications to prosthetics, exoskeletons and human-machine interaction. Current state of the art decoding methods require intensive training on a single user before it can be utilized, and have been unable to achieve both user-independence and real-time performance. This paper presents a real-time EMG classification method which generalizes across users without requiring an additional training phase. An EMG-embedded sleeve quickly positions and records from EMG surface electrodes on six forearm muscles. An optimized decision tree classifies signals from these sensors into five distinct movements for any given user using EMG energy synergies between muscles. This method was tested on 10 healthy subjects using leave-one-out validation, resulting in an overall accuracy of 79±6.6%, with sensitivity and specificity averaging 66% and 97.6%, respectively, over all classified motions. The high specificity values demonstrate the ability to generalize across users, presenting opportunities for large-scale studies and broader accessibility to EMG-driven applications.
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Ogawa, Kuniyasu, Yasuo Yokouchi, Tomoyuki Haishi, and Kohei Ito. "Measurement of Current-Density in PEFC With NMR Sensors." In ASME/JSME 2011 8th Thermal Engineering Joint Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ajtec2011-44370.
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In order to improve the power generation performance of polymer electrolyte fuel cells (PEFC), it is necessary to maintain high current density over the whole area of the membrane electrode assembly (MEA) that includes the additional Pt-carbon particles loaded on the Polymer Electrolyte Membrane (PEM) as an electrocatalyst layer. However, the current density generated at the MEA is distributed unevenly due to a lack of hydrogen, flooding, and so on. Therefore, achieving a higher current density in a PEFC requires monitoring the local current density. The local current density in a PEFC can be measured by the frequency shift of the NMR signal received from planar surface coils inserted into the PEFC as sensors. This method is based on the relationship that the spatial gradient of the frequency shifts in NMR signals along the MEA is proportional to the magnetic field strength induced by local current density. In this study, two kinds of MEA were used. One MEA was with the platinum catalyst applied to an area of 50 mm * 50 mm. The other MEA was with platinum catalyst over half this area. The distributions of the frequency shift of NMR signals in PEFCs using these two MEAs were measured. These measured distributions of the spatial gradients were in agreement with those obtained by the theoretical-analysis of magnetic fields in PEFC. The spatial distributions of current density generated in PEFCs were obtained from the spatial gradients and theoretical result.
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Caslaru, R., Y. B. Guo, and X. T. Wei. "Fabrication and Tribological Functions of Micro Dent Arrays on Ti-6Al-4V Surface by Laser Shock Peening." In ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/msec2014-4067.
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Surface patterning has become a valuable technique for fabricating micro dents which may act as lubricant reservoirs to reduce friction and wear in sliding and rolling contact applications. In this paper, the use of laser shock peening (LSP) along with an automatic X-Y table proves to be an attractive and reliable method for producing micro dent arrays with enhanced surface integrity. Surface topography and profiles of the fabricated micro dent arrays on polished Ti-6Al-4V have been characterized. The effect of dent arrays with different density on friction reduction at low and high viscosity lubrication was investigated. An acoustic emission (AE) sensor was used to on-line monitor friction and wear processes. It was found that a surface with 10% dent density provides better effect in reducing coefficient of friction (CoF) than those of smooth surface and a surface with 20% dent density. It was shown that there is a strong correlation between acoustic emissions (AE) signals, especial AE cumulative counts and wear rate.
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Du, Fenglei, Greg Bridges, D. J. Thomson, Rama R. Goruganthu, Shawn McBride, and Mike Santana. "Enhancements of Non-contact Measurements of Electrical Waveforms on the Proximity of a Signal Surface Using Groups of Pulses." In ISTFA 2002. ASM International, 2002. http://dx.doi.org/10.31399/asm.cp.istfa2002p0483.
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Abstract With the ever-increasing density and performance of integrated circuits, non-invasive, accurate, and high spatial and temporal resolution electric signal measurement instruments hold the key to performing successful diagnostics and failure analysis. Sampled electrostatic force microscopy (EFM) has the potential for such applications. It provides a noninvasive approach to measuring high frequency internal integrated circuit signals. Previous EFMs operate using a repetitive single-pulse sampling approach and are inherently subject to the signal-to-noise ratio (SNR) problems when test pattern duty cycle times become large. In this paper we present an innovative technique that uses groups of pulses to improve the SNR of sampled EFM systems. The approach can easily provide more than an order-ofmagnitude improvement to the SNR. The details of the approach are presented.
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Clapham, Lynann, and Vijay Babbar. "Effects of Detector Dynamics on Magnetic Flux Leakage Signals From Dents and Gouges." In 2012 9th International Pipeline Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/ipc2012-90551.
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The current study was designed to model the dynamic effects of detector ride and magnet liftoff on Magnetic Flux Leakage (MFL) signals from dents as well as gouges that have significant denting. The MFL tools have long been used for the detection and sizing of corrosion defects. This is comparatively straightforward for a number of reasons, one of which is that the MFL detector assembly can ride relatively smoothly along the inner pipe wall surface. This is not the case when significant denting is present, since the dent presents a perturbation in the pipe wall that can cause liftoff of the detector or magnet system. Since the tool travels at relatively high speeds down the pipe, the dent itself can cause the detector to lose contact with the trailing half of the dent. In addition, the magnet pole piece may experience partial liftoff as it traverses the dent, thus causing a change in the local flux density. In this study results from ‘static’ measurements are compared with a dynamic case in which detector liftoff is simulated through modeling and experiment. Results are discussed regarding the severity of MFL signal loss at the trailing edge of the defect as a result of detector liftoff. The effect of partial liftoff of the magnet as it passes over the dent is also examined. Magnet liftoff is found to increase the local magnetic flux near the liftoff region, causing the MFL signal from the dent wall to increase rather than decrease in the vicinity of magnet liftoff region.
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Pahuja, Rishi, and M. Ramulu. "In-Situ Monitoring in Abrasive Water Jet Machining of Stacked Titanium (Ti6Al4V)-CFRP Through Time and Frequency Analysis of Acoustic Emission Signals." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-73396.
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Abstract Hybrid metal-composite structures are widely used in aerospace industry but the machining challenges, especially at high cutting speeds, limit their employability due to higher production costs and tool wear. Abrasive Water jet (AWJ) is a viable high speed alternative, to conventional milling but the process is limited by the kerf roughness and striations, burrs and delamination. Due to difference in machining behavior of ductile metal and brittle composite, the resulting surface quality is sensitive to the use of non-optimal process parameters, and in-process faults and defects. This study explores the AWJ process monitoring in machining Ti6Al4V-CFRP stacks through Acoustic emission (AE) signals. AWJ Machining experiments were conducted with varying pressure (200, 275, 350 MPa) and traverse feed rate (15, 7.5, 10 mm/s) for two stacking configurations — Ti/CFRP and CFRP/Ti. AE signals acquired at each of these material layers were correlated with the process parameters. Signal RMS was calculated in time domain and a correlation was found with the jet power-to-speed ratio (Ė/u). Further, the AE signals were studied in frequency and simultaneous time-frequency domain. A characteristic frequency, based on an estimation of abrasive particle impacts, was calculated (222.5 kHz). This characteristic frequency band was used to monitor the surface quality. Among other features, maximum power spectral density (PSD) was found superior. Overall, a strong correlation was established between the Abrasive Water Jet process variables, AE signals and the resulting surface quality using the time-frequency spectrogram with the proposed characteristic frequency banding.