Myoelectric Control of Artificial Limbs¿Is There a Need to Change Focus? [In the Spotlight]

By Ning Jiang, S. Došen, K. Müller, Dario Farina. IEEE Signal Processing Magazine, 2012

469 citations recorded by the source corpus.

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Surface Electromyography Signal Processing and Classification Techniques (2013, background): “SVM and LDA classifiers are currently very popular amongst the researcher for the prosthetic control application due to their simple implementation and ease of training [94,95].”
Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation (2019, methodology): “This approach consists of segmentation of data, feature extraction, and classification of a set of features or patterns for the various mode of myo-activations [23,24].”
The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges (2014, background): “Among these potential options, the muscle interfacing is currently the only viable way to control external devices in commercial and clinical systems [9]–[12].”