The extraction of neural strategies from the surface EMG: an update.

By Dario Farina, Roberto Merletti, Roger M. Enoka. Journal of applied physiology, 2014

505 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/8240101eace66a2a406b27428d8aa1a1858ebdc5

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

1. Ales Holobar
2. Ning Jiang
3. Oskar C. Aszmann
4. Dario Farina
5. Bernhard Graimann
6. Hubertus Rehbaum
7. Hans Dietl

In Cellular and Molecular Neuroscience

1. Oskar C. Aszmann
2. Dario Farina
3. Ales Holobar
4. Bernhard Graimann
5. Hubertus Rehbaum
6. Ning Jiang
7. Hans Dietl

In Cognitive Neuroscience

1. Ales Holobar
2. Oskar C. Aszmann
3. Dario Farina
4. Bernhard Graimann
5. Hubertus Rehbaum
6. Ning Jiang
7. Hans Dietl

Citations in the corpus

• 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], ”