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Influence of multiple dynamic factors on the performance of myoelectric pattern recognition., , and . EMBC, page 1679-1682. IEEE, (2015)Finger Movements Classification for the Dexterous Control of Upper Limb Prosthesis Using EMG Signals., , , , and . TAROS, volume 7429 of Lecture Notes in Computer Science, page 434-435. Springer, (2012)A fusion of time-domain descriptors for improved myoelectric hand control., , , and . SSCI, page 1-6. IEEE, (2016)Myoelectric feature extraction using temporal-spatial descriptors for multifunction prosthetic hand control., , , and . EMBC, page 1696-1699. IEEE, (2016)Classification of Finger Movements for the Dexterous Hand Prosthesis Control With Surface Electromyography., , , and . IEEE J. Biomed. Health Informatics, 17 (3): 608-618 (2013)Selecting the optimal movement subset with different pattern recognition based EMG control algorithms., , and . EMBC, page 315-318. IEEE, (2016)Development of a Highly Dexterous Robotic Hand with Independent Finger Movements for Amputee Training., , , and . TAROS, volume 8069 of Lecture Notes in Computer Science, page 291-293. Springer, (2013)Combined influence of forearm orientation and muscular contraction on EMG pattern recognition., , , and . Expert Syst. Appl., (2016)A preliminary investigation of the effect of force variation for myoelectric control of hand prosthesis., , , and . EMBC, page 5758-5761. IEEE, (2013)Shoulder girdle recognition using electrophysiological and low frequency anatomical contraction signals for prosthesis control., and . CAAI Trans. Intell. Technol., 7 (1): 81-94 (2022)