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K. Nishihara, Y. Chiba, Y. Suzuki, H. Moriyama, N. Kanemura, T. Ito, K. Takayanagi & T. Gomi. (2010) Effect of position of electrodes relative to the innervation zone onsurface EMG. Journal of Medical Engineering & Technology 34:2, pages 141-147.
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Yanxu Sun & Junning Cui. (2023) Design of Wearable sEMG Acquisition Sensor and Data Gathering. Design of Wearable sEMG Acquisition Sensor and Data Gathering.
Nicoline B. M. Voet, Christiaan G. J. Saris, Dick H. J. Thijssen, Vincent Bastiaans, David E. Sluijs & Mariska M. H. P. Janssen. (2022) Surface Electromyography Thresholds as a Measure for Performance Fatigability During Incremental Cycling in Patients With Neuromuscular Disorders. Frontiers in Physiology 13.
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Eduardo Alcaraz-Mateos, Rubén Hernández-Gómez, Estefanía Rojas Calvente, Nicolás Sánchez-Campoy, Ignacio Martínez González-Moro, Fuensanta Caballero-Alemán & Enrique Poblet. (2022) Comparison of muscle activity while using different input devices in digital pathology. Revista Española de Patología 55:1, pages 19-25.
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Jianfei Zhu, Chunzhi Yi, Baichun Wei, Chifu Yang, Zhen Ding & Feng Jiang. (2021) The Muscle Fatigue’s Effects on the sEMG-Based Gait Phase Classification: An Experimental Study and a Novel Training Strategy. Applied Sciences 11:9, pages 3821.
Crossref
Crossref
Luigi Truppa, Michelangelo Guaitolini, Pietro Garofalo, Carlo Castagna & Andrea Mannini. (2020) Assessment of Biomechanical Response to Fatigue through Wearable Sensors in Semi-Professional Football Referees. Sensors 21:1, pages 66.
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Hayder A. Yousif, Ammar Zakaria, Norasmadi Abdul Rahim, Ahmad Faizal Bin Salleh, Mustafa Mahmood, Khudhur A. Alfarhan, Latifah Munirah Kamarudin, Syed Muhammad Mamduh, Ali Majid Hasan & Moaid K. Hussain. (2019) Assessment of Muscles Fatigue Based on Surface EMG Signals Using Machine Learning and Statistical Approaches: A Review. IOP Conference Series: Materials Science and Engineering 705:1, pages 012010.
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Yumiao Chen, Zhongliang Yang, Hugh Gong & Shengze Wang. (2017) Recognition of sketching from surface electromyography. Neural Computing and Applications 30:9, pages 2725-2737.
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Crossref
P.A. Karthick, Diptasree Maitra Ghosh & S. Ramakrishnan. (2018) Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms. Computer Methods and Programs in Biomedicine 154, pages 45-56.
Crossref
Crossref
R. Merletti, B. Afsharipour, J. Dideriksen & D. Farina. 2016. Surface Electromyography : Physiology, Engineering, and Applications. Surface Electromyography : Physiology, Engineering, and Applications
273
310
.
Kalyani Nair, Alfonse T. Masi, Brian J. Andonian, Alexander J. Barry, Brandon A. Coates, John Dougherty, Emily Schaefer, Jacqueline Henderson & Joseph Kelly. (2016) Stiffness of resting lumbar myofascia in healthy young subjects quantified using a handheld myotonometer and concurrently with surface electromyography monitoring. Journal of Bodywork and Movement Therapies 20:2, pages 388-396.
Crossref
Crossref
Mohamed R. Al-Mulla & Francisco Sepulveda. (2014) Super Wavelet for sEMG Signal Extraction During Dynamic Fatiguing Contractions. Journal of Medical Systems 39:1.
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Anbin Xiong, Daohui Zhang, Xingang Zhao, Jianda Han & Guangjun Liu. (2014) Classification of Gesture based on sEMG Decomposition: A Preliminary Study. IFAC Proceedings Volumes 47:3, pages 2969-2974.
Crossref
Crossref
Anirban Chowdhury, Rithvik Ramadas & Sougata Karmakar. 2013. ICoRD'13. ICoRD'13
411
421
.
Dinesh K. Kumar, Sridhar P. Arjunan & Ganesh R. Naik. (2011) Measuring Increase in Synchronization to Identify Muscle Endurance Limit. IEEE Transactions on Neural Systems and Rehabilitation Engineering 19:5, pages 578-587.
Crossref
Crossref
Luis Carrasco, Borja Sañudo, Moisés de Hoyo, Francisco Pradas & Marzo E. Da Silva. (2011) Effectiveness of low-frequency vibration recovery method on blood lactate removal, muscle contractile properties and on time to exhaustion during cycling at VO2max power output. European Journal of Applied Physiology 111:9, pages 2271-2279.
Crossref
Crossref
J. F. Sarmiento, A. B. Benevides, M. H. Moreira, A. Elias, T. F. Bastos, I. V. Silva & C. C. Pelegrina. (2011) Comparative muscle study fatigue with sEMG signals during the isotonic and isometric tasks for diagnostics purposes. Comparative muscle study fatigue with sEMG signals during the isotonic and isometric tasks for diagnostics purposes.
Mohamed R. Al-Mulla, Francisco Sepulveda & Martin Colley. (2011) A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue. Sensors 11:4, pages 3545-3594.
Crossref
Crossref
Matthew S. Tenan, Robert G. McMurray, B. Troy Blackburn, Melanie McGrath & Kyle Leppert. (2011) The relationship between blood potassium, blood lactate, and electromyography signals related to fatigue in a progressive cycling exercise test. Journal of Electromyography and Kinesiology 21:1, pages 25-32.
Crossref
Crossref
Vijay P Singh, Dinesh K Kumar, Barbara Polus, Sonia Lo Guidice & Steve Fraser. (2006) Changes in SEMG during the Long Duration Cycling Exercise. Changes in SEMG during the Long Duration Cycling Exercise.