Literatura académica sobre el tema "High density surface electromyography (HD-sEMG)"
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Artículos de revistas sobre el tema "High density surface electromyography (HD-sEMG)"
Piitulainen, Harri, Alberto Botter, Mathieu Bourguignon, Veikko Jousmäki y Riitta Hari. "Spatial variability in cortex-muscle coherence investigated with magnetoencephalography and high-density surface electromyography". Journal of Neurophysiology 114, n.º 5 (1 de noviembre de 2015): 2843–53. http://dx.doi.org/10.1152/jn.00574.2015.
Texto completoGamucci, Fiorenza, Marcello Pallante, Sybille Molle, Enrico Merlo y 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, n.º 6 (20 de marzo de 2022): 785. http://dx.doi.org/10.3390/ani12060785.
Texto completoChen, Jiangcheng, Sheng Bi, George Zhang y Guangzhong Cao. "High-Density Surface EMG-Based Gesture Recognition Using a 3D Convolutional Neural Network". Sensors 20, n.º 4 (21 de febrero de 2020): 1201. http://dx.doi.org/10.3390/s20041201.
Texto completovan Dijk, J. P., D. Kusters, N. van Alfen, M. J. Zwarts, D. F. Stegeman y G. Drost. "FC7.2 Using high-density surface electromyography (HD-sEMG) in detecting neuromuscular disorders in children". Clinical Neurophysiology 117 (septiembre de 2006): 1–2. http://dx.doi.org/10.1016/j.clinph.2006.06.025.
Texto completoFavretto, M. A., S. Cossul, F. R. Andreis, L. R. Nakamura, M. F. Ronsoni, S. Tesfaye, D. Selvarajah y 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, n.º 2 (5 de enero de 2022): 025001. http://dx.doi.org/10.1088/2057-1976/ac455b.
Texto completoLi, Yuchang, Hongqing Pan y Quanjun Song. "ADS1299-Based Array Surface Electromyography Signal Acquisition System". Journal of Physics: Conference Series 2383, n.º 1 (1 de diciembre de 2022): 012054. http://dx.doi.org/10.1088/1742-6596/2383/1/012054.
Texto completoJaber, Hanadi, Mofeed rashid y Luigi Fortuna. "Interactive Real-Time Control System for The Artificial Hand". Iraqi Journal for Electrical and Electronic Engineering 16, n.º 1 (11 de mayo de 2020): 1–10. http://dx.doi.org/10.37917/ijeee.16.1.8.
Texto completoLapatki, B. G., J. P. van Dijk, I. E. Jonas, M. J. Zwarts y D. F. Stegeman. "A thin, flexible multielectrode grid for high-density surface EMG". Journal of Applied Physiology 96, n.º 1 (enero de 2004): 327–36. http://dx.doi.org/10.1152/japplphysiol.00521.2003.
Texto completoZhang, Yingwei, Yiqiang Chen, Hanchao Yu, Xiaodong Yang, Ruizhe Sun y Bixiao Zeng. "A Feature Adaptive Learning Method for High-Density sEMG-Based Gesture Recognition". Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, n.º 1 (19 de marzo de 2021): 1–26. http://dx.doi.org/10.1145/3448114.
Texto completoGat, Liraz, Aaron Gerston, Liu Shikun, Lilah Inzelberg y Yael Hanein. "Similarities and disparities between visual analysis and high-resolution electromyography of facial expressions". PLOS ONE 17, n.º 2 (22 de febrero de 2022): e0262286. http://dx.doi.org/10.1371/journal.pone.0262286.
Texto completoTesis sobre el tema "High density surface electromyography (HD-sEMG)"
Imrani, Sallak Loubna. "Evaluation of muscle aging using high density surface electromyography". Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2647.
Texto completoWith 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
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.
Texto completoFast 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
Aresu, Federica. "Comparison of high density and bipolar surface EMG for ankle joint kinetics using machine learning". Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-294473.
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