The extraction of neural strategies from the surface EMG.
By Dario Farina, Roberto Merletti, Roger M. Enoka. Journal of applied physiology, 2004
1,609 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/25026b61bd339eb5e099fb6825438e68d05ddca6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- François Hug
- Dario Farina
- Ales Holobar
- S. Dorel
- Roger M. Enoka
- Roberto Merletti
- Ning Jiang
- Oskar C. Aszmann
In Cognitive Neuroscience
- François Hug
- Dario Farina
- Ales Holobar
- S. Dorel
- Roger M. Enoka
- Roberto Merletti
- Oskar C. Aszmann
- Mohammed R. Al-Mulla
Citations in the corpus
- Decoding the neural drive to muscles from the surface electromyogram. (2010, methodology): “As detailed issues related to classic approaches were reviewed previously (Farina et al., 2004a), this review focuses on recent developments in interpreting surface EMG amplitude and in decomposing the surface EMG to detect discharge times.”
- Repeated-Sprint Ability — Part I (2011, background): “amplitude cancellation phenomena, excessive sweat, changes in fibre membrane and motor unit properties).([126]) For instance, interpretation of EMGscores (e.”
- Electromyographic analysis of pedaling: a review. (2009, methodology): “Using this technique, Farina et al. (2004a) showed a trend of decreasing conduction velocity on VL and VM during a fatiguing cycling exercise.”
- A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue (2011, background): “study the non-stationary signals during dynamic contractions [81].”
- The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges (2014, background): “Because most myoelectric control schemes use macro-features of the surface EMG, that depend on the neural and peripheral information contained in the signal, their performance is influenced by the factors that can affect the motor unit action potential shapes or the neural drive to the muscle [23], ”
- The extraction of neural strategies from the surface EMG: an update. (2014, neutral): “ence EMG signal is influenced by the discharge characteristics of the active motor units (31, 39, 77, 95), which are neural properties.”