Enhanced myoelectric control against arm position change with weighted recursive Gaussian process
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-021-05743-y.pdf
Reference47 articles.
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2. Yang D, Gu Y, Thakor NV, Liu H (2019) Improving the functionality, robustness, and adaptability of myoelectric control for dexterous motion restoration. Exp Brain Res 237(2):291–311. https://doi.org/10.1007/s00221-018-5441-x
3. Farina D, Jiang N, Rehbaum H, Holobar A, Graimann B, Dietl H, Aszmann OC (2014) The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges. IEEE Trans Neural Syst Rehabil Eng 22(4):797–809. https://doi.org/10.1109/TNSRE.2014.2305111
4. Scheme E, Fougner A, Stavdahl Ø, Chan ADC, Englehart K (2010) Examining the adverse effects of limb position on pattern recognition based myoelectric control. In: 2010 annual international conference of the IEEE engineering in medicine and biology, pp 6337–6340
5. Geng Y, Zhou P, Li G (2012) Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees. J NeuroEng Rehabil 9(1):74. https://doi.org/10.1186/1743-0003-9-74
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1. Toward Robust, Adaptiveand Reliable Upper-Limb Motion Estimation Using Machine Learning and Deep Learning–A Survey in Myoelectric Control;IEEE Journal of Biomedical and Health Informatics;2022-08
2. Improving the Robustness of Human-Machine Interactive Control for Myoelectric Prosthetic Hand During Arm Position Changing;Frontiers in Neurorobotics;2022-06-07
3. Special issue on computational intelligence-based modeling, control and estimation in modern mechatronic systems;Neural Computing and Applications;2022-01-30
4. An Adaptive Multi-Modal Control Strategy to Attenuate the Limb Position Effect in Myoelectric Pattern Recognition;Sensors;2021-11-07
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