Auswahl der wissenschaftlichen Literatur zum Thema „High density surface electromyographic signals“
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Zeitschriftenartikel zum Thema "High density surface electromyographic signals"
Marateb, Hamid R., Monica Rojas-Martínez, Marjan Mansourian, Roberto Merletti und Miguel A. Mañanas Villanueva. „Outlier detection in high-density surface electromyographic signals“. Medical & Biological Engineering & Computing 50, Nr. 1 (23.06.2011): 79–89. http://dx.doi.org/10.1007/s11517-011-0790-7.
Der volle Inhalt der QuelleChen, Chen, Shihan Ma, Xinjun Sheng, Dario Farina und Xiangyang Zhu. „Adaptive Real-Time Identification of Motor Unit Discharges From Non-Stationary High-Density Surface Electromyographic Signals“. IEEE Transactions on Biomedical Engineering 67, Nr. 12 (Dezember 2020): 3501–9. http://dx.doi.org/10.1109/tbme.2020.2989311.
Der volle Inhalt der QuelleSong, Rui, Xu Zhang, Xi Chen, Xiang Chen, Xun Chen, Shuang Yang und Erwei Yin. „Decoding silent speech from high-density surface electromyographic data using transformer“. Biomedical Signal Processing and Control 80 (Februar 2023): 104298. http://dx.doi.org/10.1016/j.bspc.2022.104298.
Der volle Inhalt der QuelleLi, Yuchang, Hongqing Pan und Quanjun Song. „ADS1299-Based Array Surface Electromyography Signal Acquisition System“. Journal of Physics: Conference Series 2383, Nr. 1 (01.12.2022): 012054. http://dx.doi.org/10.1088/1742-6596/2383/1/012054.
Der volle Inhalt der QuelleSleutjes, B. T. H. M., M. De Vos, J. H. Blok, I. Montfoort, B. Mijović, M. Signoretto, S. Van Huffel und I. Gligorijević. „Motor Unit Tracking Using High Density Surface Electromyography (HDsEMG)“. Methods of Information in Medicine 54, Nr. 03 (2015): 221–26. http://dx.doi.org/10.3414/me13-02-0049.
Der volle Inhalt der QuelleIbrahim, Ayad Assad, Ikhlas Mahmoud Farhan und 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, Nr. 2 (01.04.2022): 1530. http://dx.doi.org/10.11591/ijece.v12i2.pp1530-1539.
Der volle Inhalt der QuelleXue, Suqi, Farong Gao, Xudong Wu, Qun Xu, Xuecheng Weng und Qizhong Zhang. „MUNIX repeatability evaluation method based on FastICA demixing“. Mathematical Biosciences and Engineering 20, Nr. 9 (2023): 16362–82. http://dx.doi.org/10.3934/mbe.2023730.
Der volle Inhalt der QuelleMartinez-Valdes, Eduardo, Francesco Negro, Deborah Falla, Alessandro Marco De Nunzio und Dario Farina. „Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles“. Journal of Applied Physiology 124, Nr. 4 (01.04.2018): 1071–79. http://dx.doi.org/10.1152/japplphysiol.01115.2017.
Der volle Inhalt der QuelleGamucci, Fiorenza, Marcello Pallante, Sybille Molle, Enrico Merlo und 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, Nr. 6 (20.03.2022): 785. http://dx.doi.org/10.3390/ani12060785.
Der volle Inhalt der QuelleHossen, A., G. Deuschl, S. Groppa, U. Heute und M. Muthuraman. „Discrimination of physiological tremor from pathological tremor using accelerometer and surface EMG signals“. Technology and Health Care 28, Nr. 5 (18.09.2020): 461–76. http://dx.doi.org/10.3233/thc-191947.
Der volle Inhalt der QuelleDissertationen zum Thema "High density surface electromyographic signals"
Imrani, Sallak Loubna. „Evaluation of muscle aging using high density surface electromyography“. Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2647.
Der volle Inhalt der QuelleWith 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
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.
Der volle Inhalt der QuelleThe 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
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.
Der volle Inhalt der QuelleFast 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
Buchteile zum Thema "High density surface electromyographic signals"
Oliveira, I. S., M. A. Favretto, S. Cossul und 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, 1829–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-70601-2_267.
Der volle Inhalt der QuelleOkada, Yoshio. „Physiological Bases of Magnetoencephalography and Electroencephalography“. In Fifty Years of Magnetoencephalography, 35–65. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190935689.003.0004.
Der volle Inhalt der QuelleBoudriki Semlali, Badr-Eddine, Carlos Molina, Mireia Carvajal Librado, Hyuk Park und 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.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "High density surface electromyographic signals"
Marateb, H. R., M. Rojas-Martinez, M. A. Mananas Villanueva und 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.
Der volle Inhalt der QuelleIlg, Julian, Lukas Hinderer, Konstantin Struebig und 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.
Der volle Inhalt der QuelleMontazerin, Mansooreh, Soheil Zabihi, Elahe Rahimian, Arash Mohammadi und 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.
Der volle Inhalt der QuelleVo-Dinh, T., und D. L. Stokes. „SERODS: A New Principle for High-Density Optical Data Storage“. In Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1994. http://dx.doi.org/10.1364/ods.1994.tud1.
Der volle Inhalt der QuelleGibson, Alison E., Mark R. Ison und 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.
Der volle Inhalt der QuelleOgawa, Kuniyasu, Yasuo Yokouchi, Tomoyuki Haishi und 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.
Der volle Inhalt der QuelleCaslaru, R., Y. B. Guo und 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.
Der volle Inhalt der QuelleDu, Fenglei, Greg Bridges, D. J. Thomson, Rama R. Goruganthu, Shawn McBride und 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.
Der volle Inhalt der QuelleClapham, Lynann, und 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.
Der volle Inhalt der QuellePahuja, Rishi, und 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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