Relevant bibliographies by topics / Signal EMG du muscle

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Signal EMG du muscle'

Author: Grafiati
Published: 8 June 2024
Last updated: 31 July 2025

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Journal articles on the topic "Signal EMG du muscle"

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Shakya, Sahaj, and Bipul Ranjitkar. "Forearm Bio-Medical Signal Processing." International Journal on Engineering Technology 2, no. 1 (2024): 49–59. https://doi.org/10.3126/injet.v2i1.72518.

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This research utilizes low-dimensional surface EMG and EEG data, obtained from the human arm using ECG electrodes, to analyze forearm muscle signals through a novel approach. Both EMG and EEG signals are employed side by side: EEG captures brain activity, particularly in the beta (13-30 Hz) and alpha (8-12 Hz) frequency ranges, while EMG focuses on muscle activity in the 20 Hz to 200 Hz range. Beta waves are associated with motor planning and voluntary movements, while alpha waves decrease during movement execution, indicating disengagement from a resting state. Event-related desynchronization
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Strzecha, Krzysztof, Marek Krakós, Bogusław Więcek, et al. "Processing of EMG Signals with High Impact of Power Line and Cardiac Interferences." Applied Sciences 11, no. 10 (2021): 4625. http://dx.doi.org/10.3390/app11104625.

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This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because the correct muscle activity measurement of strongly noised EMG signals is the major hurdle in medical applications, a raw measured EMG signal should be cleaned of different factors like power network interference and ECG heartbeat. Unfortunately, there are no completed studies showing full multistage signal processing of EMG recordings. In this article, the authors propose an original algorithm to perform muscle activity measurements based on raw measurements. The effective
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Azad Feyzullayev, Aynur Jabiyeva, Azad Feyzullayev, Aynur Jabiyeva. "STRATEGY FOR REDUCING MUSCLE FATIGUE IN THE USE OF BIOELECTRIC PROSTHESIS BASED ON ELECTROMYOGRAPHIC ANALYSIS." Caucasus-Economic and Social Analysis Journal of Southern Caucasus 63, no. 01 (2025): 25–36. https://doi.org/10.36962/cesajsc63012025-25.

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Muscle fatigue is characterised by a decrease in the ability of muscles to perform required functions, which is accompanied by accumulation of metabolites, changes in ionic balance and electrical properties of muscle tissue. These physiological changes lead to marked transformations of electromyographic (EMG) signals, including a shift of their spectrum to lower frequencies. Such changes affect the quality of signal recognition and control accuracy of bioelectric prostheses, since most myoelectric control algorithms are based on the stability of spectral and amplitude characteristics of EMG si
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Arifin, Fatchul, Tri Arief Sardjono, and Mauridhi Hery Purnomo. "THE RELATIONSHIP BETWEEN ELECTROMYOGRAPHY SIGNAL OF NECK MUSCLE AND HUMAN VOICE SIGNAL FOR CONTROLLING LOUDNESS OF ELECTROLARYNX." Biomedical Engineering: Applications, Basis and Communications 26, no. 05 (2014): 1450054. http://dx.doi.org/10.4015/s1016237214500549.

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Human voice intonation is affected by pitch and loudness. Pitch is related to the frequency of human voice, while loudness is related to the magnitude of human voice. Someone who does not have vocal cords, has no ability to produce voice. This problem is suffered by laryngectomy patients. Over half of all laryngectomy patients worldwide use electrolarynx for the rehabilitation of their speech ability. Unfortunately, the electrolarynx voice produces monotonic and flat intonation. Small changes in pitch and loudness of electrolarynx will give a better expression in laryngectomy patients. However
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Shiao, Yaojung, and Thang Hoang. "Exercise Condition Sensing in Smart Leg Extension Machine." Sensors 22, no. 17 (2022): 6336. http://dx.doi.org/10.3390/s22176336.

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Skeletal muscles require fitness and rehsabilitation exercises to develop. This paper presents a method to observe and evaluate the conditions of muscle extension. Based on theories about the muscles and factors that affect them during leg contraction, an electromyography (EMG) sensor was used to capture EMG signals. The signals were applied by signal processing with the wavelet packet entropy method. Not only did the experiment follow fitness rules to obtain correct EMG signal of leg extension, but the combination of inertial measurement unit (IMU) sensor also verified the muscle state to dis
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Merletti, R., B. Indino, T. Graven-Nielsen, and D. Farina. "Surface EMG Crosstalk Evaluated from Experimental Recordings and Simulated Signals." Methods of Information in Medicine 43, no. 01 (2004): 30–35. http://dx.doi.org/10.1055/s-0038-1633419.

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Summary Objectives: Surface EMG crosstalk is the EMG signal detected over a non-active muscle and generated by a nearby muscle. The aim of this study was to analyze the sources of crosstalk signals in surface EMG recordings and to discuss methods proposed in the literature for crosstalk quantification and reduction. Methods: The study is based on both simulated and experimental signals. The simulated signals are generated by a structure based surface EMG signal model. Signals were recorded with both intramuscular and surface electrodes and single motor unit surface potentials were extracted wi
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Neto, Osmar Pinto, and Evangelos A. Christou. "Rectification of the EMG Signal Impairs the Identification of Oscillatory Input to the Muscle." Journal of Neurophysiology 103, no. 2 (2010): 1093–103. http://dx.doi.org/10.1152/jn.00792.2009.

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Rectification of EMG signals is a common processing step used when performing electroencephalographic–electromyographic (EEG–EMG) coherence and EMG–EMG coherence. It is well known, however, that EMG rectification alters the power spectrum of the recorded EMG signal (interference EMG). The purpose of this study was to determine whether rectification of the EMG signal influences the capability of capturing the oscillatory input to a single EMG signal and the common oscillations between two EMG signals. Several EMG signals were reconstructed from experimentally recorded EMG signals from the surfa
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L N, Dayananda. "Portable Non – Invasive Device for ECG and EMG Monitoring." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48910.

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Abstract— This project proposes the design and implementation of a portable, non-invasive ECG and EMG monitoring system using the ESP32-S3 microcontroller. The system is capable of capturing and displaying real-time bioelectrical signals from the human body using two dedicated sensors—an AD8232 module for electrocardiogram (ECG) signal acquisition and a modular EMG sensor for muscle activity monitoring. The ESP32-S3’s built-in ADC is used to digitize the signals, which are then processed and displayed as scrolling waveforms on a 320×240 SPI TFT display. A push-button interface is incorporated
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Ojha, Anuj. "An Introduction to Electromyography Signal Processing and Machine Learning for Pattern Recognition: A Brief Overview." Extensive Reviews 3, no. 1 (2023): 24–37. http://dx.doi.org/10.21467/exr.3.1.8382.

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Electromyography (EMG) is about studying electrical signals from muscles and can provide a wealth of information on the function, contraction, and activity of your muscles. In the field of EMG pattern recognition, these signals are used to identify and categorize patterns linked to muscle activity. Various machine learning (ML) methods are used for this purpose. Successful detection of these patterns depends on using effective signal-processing techniques. It is crucial to reduce noise in EMG for accurate and meaningful information about muscle activity, improving signal quality for precise as
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HAMZI, Maroua, Mohamed BOUMEHRAZ, and Rafia HASSANI. "Flexion Angle Estimation from Single Channel Forearm EMG Signals using Effective Features." Electrotehnica, Electronica, Automatica 71, no. 3 (2023): 61–68. http://dx.doi.org/10.46904/eea.23.71.3.1108007.

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Electromyography (EMG) records the electrical activity generated by skeletal muscles, offering valuable insights into muscle function and movement. To address the complexity of EMG signals, various signal analysis methods have been developed in the time and frequency domains for engineering applications like myoelectric control of prosthetics and movement analysis. In this study, EMG signals were acquired from ten healthy volunteers in different forearm positions using a Myoware Muscle Sensor and MPU6050 board. From each EMG signal, root mean square (RMS), standard deviation (STD), and mean ab
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Dissertations / Theses on the topic "Signal EMG du muscle"

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Portero, Pierre. "Adaptation du muscle humain à la microgravité simulée : apport de l'analyse spectrale du signal EMG." Compiègne, 1993. http://www.theses.fr/1993COMP566S.

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Les modifications des paramètres spectraux du signal électromyographique de surface (EMGS) des muscles Triceps Surae (T. S. ) et Tibialis Anterior (T. A. ), au cours d'une épreuve de fatigue isométrique, sont étudiées en relation avec une situation de microgravité simulée chez l'homme, c'est-à-dire lors d'une période de Bed Rest (B. R. ). La revue de la littérature a permis de montrer que : d'une part, lors d'une période de microgravité réelle ou simulée, les muscles à fonction antigravitaire (T. S) sont plus affectés que les muscles à fonction phasique (T. A. ) ; d'autre part, les paramètres
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Liu, Ming Ming. "Dynamic muscle force prediction from EMG signals using artificial neural networks." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq20875.pdf.

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Moss, Christa Wheeler. "INVESTIGATION OF BELOW INJURY MUSCLE SIGNALS AS A COMMAND SOURCE FOR A MOTOR NEUROPROSTHESIS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1315924472.

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Joubert, Michelle. "A finite element model for the investigation of surface EMG signals during dynami contraction." Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-09042008-105943/.

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Ayachi, Fouaz Sofiane. "Étude du recrutement des unités motrices par analyse du signal EMG de surface." Compiègne, 2011. http://www.theses.fr/2011COMP1998.

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Le système nerveux central contrôle des mouvements par l’activation des unités de motrices (UM), les plus petites structures fonctionnelles du muscle. Les UM produisent une activité électrique qui peut être détectée par la technique de l’électromyographie de surface (EMGs). Le caractère stochastique du signal EMGs est dû principalement à la superposition des trains de potentiels d’action d’UM (TPAUM) (recrutement spatial), les TPAUM sont caractérisés par leurs instants de décharge (recrutement temporel), ainsi que par la forme des potentiels d’action (PA), qui dépend de certains facteurs métho
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KHALIL, ULLAH XXX. "Extraction of Muscle Anatomical and Physiological Information from Multi-Channel Surface EMG Signals: Applications in Obstetrics." Doctoral thesis, Politecnico di Torino, 2016. http://hdl.handle.net/11583/2642318.

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Motor Unit (MU) innervation zones (IZs) localization is an important step in several clinical and non-clinical applications including 1) Acquisition of sEMG signal for accurate estimation of its amplitude and other parameters by avoiding placing the electrodes on IZs, 2) Accurate estimation of the EMG-Force relationship, 3) Effective injection of Botulinum Toxin in Post-stroke Spasticity near the IZs, and 4) Guiding the obstetricians to perform episiotomy during child delivery by avoiding cutting near the IZs of External Anal Sphincter (EAS) muscle. The minimal invasive way to identify the loc
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Rahman, Md Arifur. "A comparative study to explore the advantages of passive exoskeletons by monitoring the muscle activity of workers." Thesis, Högskolan i Gävle, Avdelningen för elektroteknik, matematik och naturvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-35150.

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Manufacturing and construction workers undertake physically strenuous activities increasing the risk of health problems, disability, and sick leave, leading to lower job attractiveness and job candidate scarcity. In the EU, up to 44 million workers are affected by workplace-related musculoskeletal disorders (MSDs), representing a total annual cost of more than €240 billion. Exoskeleton use could alleviate muscle peak loads and reduce the risks of injury of workers. This work is related to the INTERREG's project "EXSCALLERATE" which aimed to accelerate the adoption of exoskeletons among SMEs. T
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Rojas, Martínez Mónica. "Analysis of forearm muscles activity by means of new protocols of multichannel EMG signal recording and processing." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/124507.

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Los movimientos voluntarios del cuerpo son controlados por el sistema nervioso central y periférico a través de la contracción de los músculos esqueléticos. La contracción se inicia al liberarse un neurotransmisor sobre la unión neuromuscular, iniciando la propagación de un biopotencial sobre la membrana de las fibras musculares que se desplaza hacia los tendones: el Potencial de Acción de la Unidad Motora (MUAP). La señal electromiográfica de superficie registra la activación continua de dichos potenciales sobre la superficie de la piel y constituye una valiosa herramienta para la investigaci
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Cao, Hua. "Modélisation et évaluation expérimentale de la relation entre le signal EMG de surface et la force musculaire." Compiègne, 2010. http://www.theses.fr/2010COMP1856.

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L’estimation de la force générée par un muscle est importante dans les études biomécaniques et pour les applications cliniques. Puisque cette force ne peut pas être mesurée directement, le signal électromyographique de surface (SEMG), reflétant le niveau d’activation musculaire, est utilisé pour quantifier la force développée. Cependant, tous les facteurs, contrôlant une contraction isométrique, n’influencent pas la force et le SEMG simultanément. Le but de ce travail de thèse est donc de développer un modèle de simulation conjointe du SEMG et de la force, afin d’étudier la relation EMG-force.
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Grönlund, Christer. "Spatio-temporal processing of surface electromyographic signals : information on neuromuscular function and control." Doctoral thesis, Umeå universitet, Institutionen för strålningsvetenskaper, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-958.

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During muscle contraction, electrical signals are generated by the muscle cells. The analysis of those signals is called electromyography (EMG). The EMG signal is mainly determined by physiological factors including so called central factors (central nervous system origin) and peripheral factors (muscle tissue origin). In addition, during the acquisition of EMG signals, technical factors are introduced (measurement equipment origin). The aim of this dissertation was to develop and evaluate methods to estimate physiological properties of the muscles using multichannel surface EMG (MCsEMG) signa
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Books on the topic "Signal EMG du muscle"

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B, Bolton T., and Tomita T, eds. Smooth muscle excitation. Harcourt Brace, 1996.

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Raeburn, David, and Mark A. Giembycz, eds. Airways Smooth Muscle: Neurotransmitters, Amines, Lipid Mediators and Signal Transduction. Birkhäuser Basel, 1995. http://dx.doi.org/10.1007/978-3-0348-7504-2.

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Raeburn, David, and Mark A. Giembycz, eds. Airways Smooth Muscle: Peptide Receptors, Ion Channels and Signal Transduction. Birkhäuser Basel, 1995. http://dx.doi.org/10.1007/978-3-0348-7362-8.

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1953, Raeburn D., and Giembycz M. A. 1961-, eds. Airways smooth muscle: Neurotransmitters, amines, lipid mediators, and signal transduction. Birkhauser Verlag, 1995.

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Kelly, James Anthony. Aspects of signal transduction in bovine lymphatic smooth muscle cells. University College Dublin, 1996.

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1953-, Raeburn D., and Giembycz M. A. 1961-, eds. Airways smooth muscle: Peptide receptors, ion channels, and signal transduction. Birkhäuser Verlag, 1995.

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Yamada Conference on Calcium as Cell Signal (1994 Tokyo, Japan). Calcium as cell signal: Proceedings of the Yamada Conference XXXIX on Calcium as Cell Signal, April 26-28, 1994, Tokyo, Japan. Igaku-Shoin, 1996.

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Oldenhof, Alexandra Dianne. Effects of mechanical stretch on signal transduction and gene expression in myometrial smooth muscle cells. National Library of Canada, 2001.

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A, Sassoon D., ed. Stem cells and cell signalling in skeletel myogenesis. Elsevier, 2002.

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Maximum speed of forearm flexion practice effects upon surface EMG signal characteristics. 1985.

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Book chapters on the topic "Signal EMG du muscle"

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Jauw, Veronica Lestari, and S. Parasuraman. "Investigation on Upper Limb’s Muscle Utilizing EMG Signal." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35197-6_24.

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Tengshe, Richa, Anubhav Sharma, Harshbardhan Pandey, G. S. Jayant, Laveesh Pant, and Binish Fatimah. "Automated Detection for Muscle Disease Using EMG Signal." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8563-8_16.

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Barbero, Marco, Roberto Merletti, and Alberto Rainoldi. "Features of the Two-Dimensional sEMG Signal: EMG Feature Imaging." In Atlas of Muscle Innervation Zones. Springer Milan, 2012. http://dx.doi.org/10.1007/978-88-470-2463-2_6.

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Cárdenas-Guaraca, Tatiana Dolores, Danilo Andrés Molina-Vidal, and Vladimir Espartaco Robles-Bykbaev. "JointCare: An Integrated Platform for EMG Signal Analysis in Knee Osteoarthritis Rehabilitation." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-87065-1_11.

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Abstract Knee osteoarthritis represents a medical care challenge, requiring tools that improve the accuracy of monitoring during rehabilitation. The tools found present limitations for a complete analysis. In this perspective, we developed a platform to analyze electromyography (EMG) signals stored on file or captured online by an acquisition module. To evaluate the platform, an EMG acquisition of four leg muscles of a healthy subject was performed. Also, EMG signals from the database were used to visualize and calculate typical values used for EMG rehabilitation analysis. The interface allowe
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Mohd Azli, Muhammad Amzar Syazani, Mahfuzah Mustafa, Rafiuddin Abdubrani, Amran Abdul Hadi, Syarifah Nor Aqida Syed Ahmad, and Zarith Liyana Zahari. "Electromyograph (EMG) Signal Analysis to Predict Muscle Fatigue During Driving." In Proceedings of the 10th National Technical Seminar on Underwater System Technology 2018. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3708-6_35.

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Ibrahim, A. F. T., V. R. Gannapathy, L. W. Chong, and I. S. M. Isa. "Analysis of Electromyography (EMG) Signal for Human Arm Muscle: A Review." In Lecture Notes in Electrical Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24584-3_49.

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Jemaa, Olfa, Sami Bennour, David Daney, and Lotfi Romdhane. "Experimental Analysis of Electromyography (EMG) Signal for Evaluation of Isometric Muscle Force." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-27146-6_20.

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Mishra, Ram Kinker, and Rina Maiti. "Non-Linear Signal Processing Techniques Applied on EMG Signal for Muscle Fatigue Analysis During Dynamic Contraction." In CIRP Design 2012. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4507-3_19.

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Triantaphyllou, Evangelos. "First Case Study: Predicting Muscle Fatigue from EMG Signals." In Data Mining and Knowledge Discovery via Logic-Based Methods. Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1630-3_14.

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Nakajima, Y., S. Yoshinari, and S. Tadano. "Surface Conduction Analysis of EMG Signal from Forearm Muscles." In IFMBE Proceedings. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92841-6_472.

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Conference papers on the topic "Signal EMG du muscle"

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Zîrnă, Bianca-Alexandra, Denis Mihailovschi, and Mădălin Corneliu Frunzete. "EMG Signal Acquisition and Processing for Muscle Contraction Classification." In 2024 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA). IEEE, 2024. http://dx.doi.org/10.23919/spa61993.2024.10715620.

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Otero Argel, Karolina María, Jereminth Muñoz De la Torre, and Juan Monroy Lasso. "System for Data Acquisition and Measurement of Muscle Strength Using EMG Signals." In 2024 3rd International Congress of Biomedical Engineering and Bioengineering (CIIBBI). IEEE, 2024. https://doi.org/10.1109/ciibbi63846.2024.10784671.

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Prajapati, Vaibhav, Anish C. Turlapaty, Himangshu Sarma, and Mrinmoy Ghorai. "Relating Muscle Activity and Mouse Sensitivity in FPS Game Players Using Surface EMG Signals." In 2024 5th International Conference on Biomedical Engineering (IBIOMED). IEEE, 2024. https://doi.org/10.1109/ibiomed62485.2024.10875806.

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Luo, Mingze, Guowei Huang, and Longhan Xie. "The Effects of a Knee-Joint Energy Harvester on Muscle Activation in the Human Lower Limbs Based on EMG Signal." In 2025 International Conference on Electrical Automation and Artificial Intelligence (ICEAAI). IEEE, 2025. https://doi.org/10.1109/iceaai64185.2025.10956994.

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Yuwono, Dhiannisa Shabrina, Rachmad Setiawan, and Nada Fitrieyatul Hikmah. "Delayed Onset Muscle Soreness Analysis based on Discrete Wavelet Transform of EMG Signals on Leg Workout." In 2024 International Seminar on Intelligent Technology and Its Applications (ISITIA). IEEE, 2024. http://dx.doi.org/10.1109/isitia63062.2024.10668303.

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Romanova, N. "Electromyographic Signal as Feedback for Pelvic Floor Muscle Rehabilitation and Training." In European Institute for Innovation Development International Conference "Actual Issues of Modern Science". Romanova, N., 2025. https://doi.org/10.61726/7877.2025.76.41.001.

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In the present world, most people are engaged in routine office work. This factor contributes to high inactivity in the musculoskeletal system and the body. Disorders of the muscular structure and pelvic ligaments may also be caused by dyssynergic defecation, surgical intervention, degenerative disease, pregnancy and childbirth in women, muscle relaxants, narcotics, and similar factors. Therefore, developing physiotherapy methods and a fitness training plan is a highly relevant task today. The novelty of this research lies in developing a new approach to rehabilitating and training pelvic floo
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Forshaw, Robert V., Nicholas W. Snow, Jared M. Wolff, Mansour Zenouzi, and Douglas E. Dow. "Electromyography (EMG) Controlled Assistive Rehabilitation System." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-40238.

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Electromyography (EMG) is a method for monitoring the electrical activity of skeletal muscles. The EMG signal is used to diagnose neuromuscular diseases and muscular injuries. EMG can also be utilized as an indicator of user intent for a muscle contraction for a specific motion. This input signal could be used to control powered exoskeleton prostheses. Limbs with impaired motor function tend to have increased disuse that may result in further muscle weakness. Therapy and other physical activities that increase the use of an impaired limb may contribute to some recovery of motor function. A dev
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Cakir, Ozlem, Mehmet Engin, Erkan Zeki Engin, and Ufuk Yumrukaya. "Investigation of Muscle Fatigue by Processing EMG Signal." In 2009 14th National Biomedical Engineering Meeting. IEEE, 2009. http://dx.doi.org/10.1109/biyomut.2009.5130354.

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Alim, Onsy Abdul, Mohamed Moselhy, and Fatima Mroueh. "EMG signal processing and diagnostic of muscle diseases." In 2012 2nd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA). IEEE, 2012. http://dx.doi.org/10.1109/ictea.2012.6462866.

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Slack, Paul S., and Xianghong Ma. "Determination of Muscle Fatigue Using Dynamically Embedded Signals." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-34287.

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There is concern associated with the duration that a microsurgeon operates. Muscle fatigue can present itself over time and adversely affect the surgeon’s ability to perform appropriately during lengthy procedures. This paper explores a new method of analyzing muscle fatigue within the muscles predominantly used during micro-surgery. The captured Electro-MyoGraphic (EMG) data retrieved from these muscles are analyzed for any defining patterns relating to muscle fatigue. The analysis consists of dynamically embedding the EMG signals from a single muscle channel into an embedded matrix. The musc
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Reports on the topic "Signal EMG du muscle"

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Funkenstein, Bruria, and Shaojun (Jim) Du. Interactions Between the GH-IGF axis and Myostatin in Regulating Muscle Growth in Sparus aurata. United States Department of Agriculture, 2009. http://dx.doi.org/10.32747/2009.7696530.bard.

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Growth rate of cultured fish from hatching to commercial size is a major factor in the success of aquaculture. The normal stimulus for muscle growth in growing fish is not well understood and understanding the regulation of muscle growth in fish is of particular importance for aquaculture. Fish meat constitutes mostly of skeletal muscles and provides high value proteins in most people's diet. Unlike mammals, fish continue to grow throughout their lives, although the size fish attain, as adults, is species specific. Evidence indicates that muscle growth is regulated positively and negatively by
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Volunteer Kinematics and Reaction in Lateral Emergency Maneuver Tests. SAE International, 2013. http://dx.doi.org/10.4271/2013-22-0013.

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It is important to understand human kinematics and muscle activation patterns in emergency maneuvers for the design of safety systems and for the further development of human models. The objective of this study was to quantify kinematic behavior and muscle activation in simulated steering tests in several realistic conditions. In total 108 tests were performed with 10 volunteers undergoing purely lateral maneuvers at 5 m/s2 deceleration or simulated lane change maneuvers at 5 m/s2 peak acceleration and peak yaw velocity of 25 °/s. Test subjects were seated on a rigid seat and restrained by a 4
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