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Editorial
. 2020 Apr 1;10(2):129-130.
doi: 10.31661/jbpe.v0i0.2002-1076. eCollection 2020 Apr.

Recent Advances in EMG Pattern Recognition for Prosthetic Control

Affiliations
Editorial

Recent Advances in EMG Pattern Recognition for Prosthetic Control

Ameri A et al. J Biomed Phys Eng. .
No abstract available

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Conflict of interest statement

Conflict of Interest: None

References

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    1. Scheme E, Englehart K. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. Journal of Rehabilitation Research & Development. 2011;48(6):643–59. doi: 10.1682/jrrd.2010.09.0177. - DOI - PubMed
    1. Jiang N, Dosen S, Muller K-R, Farina D. Myoelectric control of artificial limbs—is there a need to change focus?[In the spotlight] IEEE Signal Processing Magazine. 2012;29(5):150–2. doi: 10.1109/MSP.2012.2203480. - DOI
    1. Ameri A, Akhaee M A, Scheme E, Englehart K. Real-time, simultaneous myoelectric control using a convolutional neural network. PloS one. 2018;13(9):e0203835. doi: 10.1371/journal.pone.0203835. [ PMC Free Article ] - DOI - PMC - PubMed
    1. Ameri A, Englehart K B, Parker P A, editors. A comparison between force and position control strategies in myoelectric prostheses. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; San Diego, CA, USA : 2012. pp. 1342–5. - DOI - PubMed

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