Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations

Author:

Phinyomark Angkoon,Campbell Evan,Scheme Erik

Publisher

Springer Singapore

Reference121 articles.

1. Al-Timemy, A.H., Bugmann, G., Escudero, J., Outram, N.: A preliminary investigation of the effect of force variation for myoelectric control of hand prosthesis. In: Proceedings of 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5758–5761 (2013). https://doi.org/10.1109/EMBC.2013.6610859

2. Al-Timemy, A.H., Khushaba, R.N., Bugmann, G., Escudero, J.: Improving the performance against force variation of emg controlled multifunctional upper-limb prostheses for transradial amputees. IEEE Trans. Neural Syst. Rehabil. Eng. 24(6), 650–661 (2016). https://doi.org/10.1109/TNSRE.2015.2445634

3. Amsüss, S., Paredes, L.P., Rudigkeit, N., Graimann, B., Herrmann, M.J., Farina, D.: Long term stability of surface EMG pattern classification for prosthetic control. In: Proceedings of 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3622–3625 (2013). https://doi.org/10.1109/EMBC.2013.6610327

4. Arjunan, S.P., Kumar, D.K.: Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors. J. NeuroEng. Rehabil. 7(1), 53 (2010). https://doi.org/10.1186/1743-0003-7-53

5. Asogbon, M.G., Samuel, O.W., Geng, Y., Idowu, P.O., Chen, S., R, N.G., Feng, P., Li, G.: Enhancing the robustness of EMG-PR based system against the combined influence of force variation and subject mobility. In: Proceedings 2018 3rd Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), pp. 12–17 (2018). https://doi.org/10.1109/ACIRS.2018.8467236

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